High Speed Rail London to the West Midlands and Beyond. HS2 Demand Model Analysis

Transcription

1 High Speed Rail London to the West Midlands and Beyond HS2 Demand Model Analysis February 2010

2 While High Speed Two (HS2) Limited has made every effort to ensure the information in this document is accurate, HS2 Ltd does not guarantee the accuracy, completeness or usefulness of the information contained in this document and it cannot accept liability for any loss or damages of any kind resulting from reliance on the information or guidance this document contains. Copyright, High Speed Two (HS2) Limited, Copyright in the typographical arrangements rests with HS2 Limited. This publication, excluding logos, may be reproduced free of charge in any format or medium for non-commercial research, private study or for internal circulation within an organisation. This is subject to it being reproduced accurately and not used in a misleading context. The title must be acknowledged as copyright and the title of the publication specified. For any other use of this material please contact HS2 Limited on , or by at [email protected], or by writing to HS2, 3rd Floor, 55 Victoria Street, London, SW1H 0EU. Further copies of this report can be obtained from ISBN: Unless specified, all maps, tables, diagrams and graphs in this report are a product of HS2 and its consultants.

3 HS2 Demand Model Analysis: Contents Contents Chapter 1: Introduction and Background Data Introduction to this report Acknowledgements The Demand for Transport and Context for HS Demand and Appraisal Helping with Scheme Design...14 Chapter 2: Demand Model Structure and Development Introduction PLANET Long Distance PLANET South and Midlands Heathrow Access Model International Rail Model Additional Modelling Evidence...27 Chapter 3: Our Assumptions and Approach Introduction Demand Growth Assumptions Passenger Preferences and the Treatment of HSR in the Demand Model Measuring Reliability Impacts of HSR Premium Fares Model Applying the HS2 Service Specification Economic Appraisal...38 Chapter 4: Central London Station Location Introduction Choosing a London Station Location Analysis of Euston...44 Chapter 5: London Interchange Station Location Introduction Options for a London Interchange Station The Potential Markets for a London Interchange Station Comparison of Heathrow and Old Oak Common Interchange Stations...55 Chapter 6: Intermediate Station Location Introduction Determining a Location...61 Chapter 7: Central Birmingham Station Location Introduction The Impact of HS Chapter 8: Birmingham Interchange Station Location Introduction Option Sifting An Interchange near Birmingham International Demand and Benefits of Birmingham Interchange

4 HS2 Demand Model Analysis Chapter 9: Connections to High Speed One Introduction Our Approach to Modelling International Demand Analysis of Different International Connections and Services Appraisal of Journey Time Benefits International Connections as Part of a Wider Network...87 Chapter 10: The Overall Business Case for HS Introduction Passenger Demand for HS HS2 Appraisal Costs Appraisal of Benefits from HS Wider Economic Impacts of HS Impact of HS2 on Carbon Emissions HS2 Value for Money Chapter 11: Appendix 1: Appendix 2: Appendix 3: Appendix 4: A Long Term Strategy for High Speed Rail Introduction Long Distance travel in Great Britain Long Term High Speed Networks Wider Networks - Modelling Approach Demand and Benefits of a Long Term Strategy Benefit Cost Ratios of a Wider Network Limitations of Our Analysis and Further Work Extensions to Manchester and Leeds Transport Economic Efficiency Tables A1.1 Introduction Sensitivity Tests on HS2 Central Case A2.1 Testing Our Assumptions A2.2 Changing the forecast level of demand for long distance rail trips A2.3 Changing Background Demand Growth and Prices on Non-Rail Modes A2.4 Premium Fares A2.5 Comparison with a classic line A2.6 Reliability High Speed Rail and Spatial Patterns and Strategies in Cities and Regions A3.1 Introduction A3.2 Why Does Spatial Impact (Land Use Change) Matter? A3.3 How Might HS2 Affect Land Use? A3.4 The Evidence of Land Use Change and HSR A3.5 Conclusions A3.6 References Service Specification for Wider Network Tests

5 Chapter 1: Introduction and Background Data

6 HS2 Demand Model Analysis 1.1 Introduction to this report High Speed Two Ltd was established in January 2009 to develop proposals for a new high speed railway line between London and the West Midlands and to consider the case for high speed rail services linking London, northern England and Scotland This report provides further detail on the approach and forecasts of demand used to support High Speed Rail: London to the West Midlands and Beyond (henceforth HS2 s report ). It explains how demand forecasting and appraisal has been used to inform and support the design of the preferred scheme, and provides detail on the expected demand and economic impact of a new high speed rail line Chapter 1 provides the context for HS2 by showing the underlying demand for transport and explains how we used analysis and appraisal to inform the design of HS2. Chapters 2 and 3 consider the modelling approach and the key assumptions that underpin our results, as well as the implications of some of these for the overall results. Chapters 4 to 9 then set out the results of our analysis and the implications for the component parts of the scheme: A Central London station. A Heathrow/Crossrail Interchange station. A Central Birmingham station. An interchange or parkway station in the West Midlands. The case for an intermediate station between London and the West Midlands. The case for a link between HS1 and HS2 and the likely passenger market for international rail connections Chapter 10 draws this together into an overall assessment of the preferred scheme that is set out in HS2 s Business Case. The report concludes with a strategic level analysis of the possible long term strategy and the implications of this for extensions to Leeds and Manchester. 6

7 Chapter 1: Introduction and Background Data 1.2 Acknowledgements Throughout the year we have worked closely with a number of organisations whose specialist and local knowledge has helped to inform our investigation. We have sought to ensure a proper process of quality assurance is in place to validate our approach and results. This has been particularly important given the UK s relative inexperience in appraising and delivering domestic high speed rail projects although we have been able to draw on the UK s growing experience in the delivery of other major projects We are grateful to Prof. Robert Cochrane, Prof. Stephen Glaister CBE, Prof. Peter Mackie, Prof Henry Overman, Dr David Simmonds and Prof. Roger Vickerman who as members of our Analytical Challenge Panel provided independent expert scrutiny on the modelling and appraisal of HS2. Their advice has been invaluable as we formulated our approach and findings. However, our findings are ours alone. There is no intention that the Challenge Panel should be seen as accountable for the conclusions that, ultimately, we alone have reached We have also commissioned specialist consultancy advice on a range of topics. Those who have advised us are listed below and their reports make up several of the supporting documents published alongside the report. WS Atkins plc Sinclair Knight Merz Pty Ltd Arup Group Ltd John Bates Dr Dan Graham & Patricia Melo Reg Harman Demand Modelling and Appraisal - (subcontracted by WS Atkins) Advice on the assessment of wider economic impacts Advice on the spatial impacts of high speed rail 7

8 HS2 Demand Model Analysis 1.3 The Demand for Transport and Context for HS The demand for transport has grown substantially over time. As people become richer they tend to travel further and more often and, as the transport network has grown, so it has become easier to travel. The total distance travelled by passengers on all modes has grown by 36% in the last 20 years as shown in figure 1.3a. Figure 1.3a - Passenger Travel (All Modes) Billion Passenger km Year Total Passenger Travel Cars, Vans and Taxis Other Source: Department for Transport (DfT) Transport Trends This growth has been driven primarily by increasing car traffic which accounts for almost 85% of the overall distance travelled. However in the last 15 years or so, there has also been rapid growth in the number of passengers, and distance travelled, on the UK s railways. The number of passenger km on rail has increased by just over 70% during this period, compared to less than 15% for cars as shown in Figure 1.3b. 8

9 Chapter 1: Introduction and Background Data Figure 1.3b - Total Passenger Travel by Rail Billion Passenger km Year Source: Office of the Rail Regulator (ORR) National Rail Trends Similarly, long distance trips of over 50 miles have been growing in line with recent trends, with an increase of more than 30% since This rapid growth is forecast to continue, with trips into and out of London being particularly important. Table 1.3 summarises the growth forecast using standard industry tools (Passenger Demand Forecasting Handbook (PDFH), version 4.1). These form the basis of the forecasts we have used in our modelling and the assumptions underpinning this are outlined in Chapter 3. 9

10 HS2 Demand Model Analysis Table 1.3 Forecast growth in long distance travel Passenger Demand per weekday to and from Central London (two way flow) 2008 Demand 2033 Demand % Growth Birmingham 5,700 13, % Manchester 5,300 14, % Leeds 4,400 12, % Glasgow 800 2, % Liverpool 2,100 5, % Newcastle 2,400 6, % Edinburgh 1,700 5, % Source: Atkins Baseline forecasting report (PLD) Such substantial increases in demand will increase passenger flows and crowding on the West Coast Main line (WCML). In 2008 there were approximately 45,000 long distance passengers per day using inter-city trains on the southern section of the WCML, with an average train loading across the whole day of 51%. By 2033 long distance demand on the WCML is expected to more than double. Although the Pendolino trains currently running on the WCML would have been lengthened to 11 cars, the average train loading would have increased to around 80%. This is an average figure, with trains during the peak times likely to have even higher loadings The following maps show the number of long distance trips on the WCML in 2008 and the increase in those volumes by Figure 1.3e shows the load factor on long distance journeys on the WCML by 2033 based on our reference case assumptions about what would happen in the future without HS HS2 offers the opportunity not only to speed up journeys for passengers along the line of the WCML, but also to provide substantial additional capacity to Birmingham and on long distance trains north of Birmingham. And the capacity released by HS2 can be reused to reduce crowding on short distance services into London. 10

11 Chapter 1: Introduction and Background Data Figure 1.3c - WCML Long Distance Daily Rail Trips in 2008 Long distance daily trips on the WCML in 2008 Source: Atkins PLANET Long Distance 11

12 HS2 Demand Model Analysis Figure 1.3d - WCML Long Distance Daily Rail Trips in 2033 Glasgow G a w Edinburgh i n u Forecast of long distance daily trips on the WCML in ,867, Newcastle N w c s York o k e d s ul l Liverpool L i p ooll 0 n ch e t r Sheffield e fii 2 21,688 1, Stoke-on-TrentS ok e on -Trer n t Nottingham tin gh , ei c t r P Peterborough t r b o o u g h rm in g h m , DM Flow Volume Legend More Than 30,000 20,000 to 30,000 10,000 to 20,000 3,000 to 10,000 Less than 3,000 Bristol B i s o l Oxford d ReadingR d ng nd on Source: Atkins PLANET Long Distance 12

13 Chapter 1: Introduction and Background Data Figure 1.3e - WCML Long Distance Load Factors in 2033 lasg o w 55 Edinburgh i u g h 62 2 Forecast of laverage daily load factors on long distance WCML services in Newcastle t e 7 York k 86 LeedsL eed s HullH u Manchester M s Liverpool L i ol l 60 Sheffield f d Stoke-on-TrentS ok e on -Trer n t NottinghamN ot n gh am ei c t r Peterborough P b orouo u g h Birmingham r i Do Minimum Crowding Legend (Volume over seats) More than 80% 60% to 80% 40% to 60% 20% to 40% 0 to 20% diffd f Bristol i l xf o r d Reading R a d n g 80 0 London o n Source: Atkins PLANET Long Distance 13

14 HS2 Demand Model Analysis 1.4 Demand and Appraisal Helping with Scheme Design The appraisal of transport impacts is a powerful tool not only to aid the justification of a scheme but also to support its design to ensure it maximises value for money. There are many trade-offs in designing a scheme, with individual components impacting on each other, and impacting on the overall experience of transport users. HS2 is no exception. For example, whether to include an intermediate station involves trading off the benefits to local passengers against costs of building the station (and re-routing the line), delays for other passengers and impacts on the capacity of the line. Appraisal techniques can help to weigh these costs and benefits. Box 1 provides a brief background to appraisal and what it attempts to capture We have sought throughout the process to ensure our assessment of the benefits of HS2 appropriately reflects the evidence available, and to weigh these against costs and environmental impacts to ensure that the resulting scheme maximises value for money. This has had implications in a number of areas, including: Location of stations. The location of a station will affect its accessibility, and so the attractiveness of a station for long distance passengers. This in turn has implications for demand, revenues and benefits which need to be weighed against the cost and constructability of these stations. Inclusion of non-core stations. We were asked to consider the potential for intermediate stations and interchange stations along the line of route, where these added to the business case. Appraisal helps to weigh the benefits and costs of such stations, and whether they can improve the business case for HS2. Line of route and service patterns. By considering the impact on demand and benefits of different journey times we ensured an appropriate trade-off between the cost of the overall HS2 route against the journey time offered by different elements of the scheme. This also helped to inform the service patterns and line of route, with fast links to London being identified as a key factor. The use of released capacity. We examined how line capacity on the existing West Coast Main Line might be re-used to provide further benefits. 14

15 Chapter 1: Introduction and Background Data Box 1 - What is Appraisal? Appraisal is an important tool to help Government assess the input of policies and investment. It helps support policy development and ensures the proper use of public resources. The guidance for appraisal across Government is set out in The Green Book: Appraisal and Evaluation in Central Government (HMT, 2003). Transport has a long history in appraisal, and DfT sets out its own guidance on appraising transport schemes which applies Green Book principles to transport investment. This guidance is set out in WebTAG (available on the DfT website). WebTAG provides a methodology to assess all of the impacts of a transport scheme both positive and negative. These range from impacts on transport users through to impacts on local communities (e.g. noise or air quality changes), environmental effects on landscape and the global effects - Greenhouse Gas emissions and climate change. The focus of this technical annex is on the assessment of impacts on transport users, most of which can be modelled, quantified and valued. Our Appraisal of Sustainability addresses the wider impacts covered by WebTAG. WebTAG s assessment of impacts on transport users considers the whole journey experience. It includes: how long a journey takes, including the impact of congestion and delays on the road network the financial costs (fares, fuel) the other costs imposed during a journey e.g. having to stand on public transport Each of these impacts has a value to transport users they would prefer to have faster journeys or less crowding on trains. Transport appraisal attempts to quantify the impacts of a transport scheme and so the value of these benefits to transport users. In the appraisal of HS2 we consider the potential for: faster, more reliable and less crowded journeys using HS2 less crowding from use of released capacity on the classic rail network the reduction in congestion (and so faster car trips) for all car users as a result of mode shift Throughout the analysis in this technical annex we consider the trade-offs for different users under different options. For example we consider the time penalty (cost of a slower journey) of stopping at a station compared to the benefits (e.g. faster journeys) of those who would have access to HS2 as a result of the station. In identifying and quantifying these trade-offs we can design a scheme which maximises the benefits of HS2 across all transport users and society in general. 15

16 HS2 Demand Model Analysis We took an incremental approach to analysis and appraisal, building on the evidence base and modelling capabilities as they were developed to enable early decisions to be made and effective prioritisation of work. There were three clear stages to this work. Stage One: High Level Demand Analysis During the first few months of the project, we used existing data and evidence sources to help provide an initial high level or strategic understanding of the key issues. Known as a Ready Reckoner, this simple analysis allowed us to quickly gain a high level understanding of current and future demand. It allowed us to conduct: A high level assessment of the patterns of demand for long distance trips. This included analysis of: i. The overall pattern of long distance trips, particularly between London and other major cities in the north of the UK. ii. Where trips started or ended within London and the West Midlands. iii. The most suitable locations for intermediate stations between Birmingham and London, and their potential to capture demand. Simple tests on the likely level of demand between different locations that might be generated by HS2. This analysis was undertaken using simple elasticities with respect to journey times and other variables. Simple analysis of what the key drivers of the HS2 business case were most likely to be This high level analysis provided early support for decisions taken around: The need for a city centre terminus at either end of HS2. The locations to consider in further detail for an intermediate station. The need to utilise capacity on the line (a few trains per hour would not be sufficient to generate a business case). The potential areas to consider in the Longer Term Strategy network designs. 16

17 Chapter 1: Introduction and Background Data Stage Two: Early Modelling Early model runs using development or prototype versions of the demand model also allowed high level analysis of the potential case for HS2, and gave an early indication of the key drivers of benefits. This assessment provided robust evidence to support comparative analysis of different options, and to provide useful information on emerging patterns of demand and benefits. Particular analysis included: Analysis of the impact of journey time benefits. Early tests suggested that reducing journey times by one minute would provide benefits of around m (present value discounted over 60 years in 2009 prices) on a fully utilised high speed line. Box 1 highlights that people value faster journeys, and using initial projections of demand we were able to estimate this overall figure for the likely value HS2 passengers as a whole would place on slight changes to journey times. This supported decisions taken on the line of route demonstrating the importance of journey times for comparison against costs (e.g. tunnelling) and environmental constraints. It also showed the potential disbenefits of stopping trains at intermediate and interchange stations. Analysis of the service pattern of HS2 trains. Simple extrapolation (based on wait times) tested the strategic implications of increasing/reducing frequencies to different stations. Analysis of the pattern of benefits from different stations. The analysis helped to identify the importance of stations served by HS2, with Birmingham, Manchester, Liverpool and Glasgow representing the bulk of demand and benefits on the west coast main line. Comparison of different options for the design of HS2. This provided comparisons of the relative benefits of different locations for interchange stations in London and Birmingham, and an intermediate station. This analysis allowed us to focus our design efforts in advance of final model tests. Stage Three: Detailed Modelling The final version of the model was then used to provide an overall assessment of the preferred scheme, as well as to confirm the incremental impacts of the key components of the scheme. Several model runs were undertaken, including: HS2 central case ( Day One scenario, with all preferred components included). No interchange station at Old Oak Common. Alternative options for a London Interchange Station in the vicinity of Heathrow. No Interchange station at Birmingham International. A test of the impact of running at classic line speeds (125mph) The economic results of these tests are described later in this report with the full results provided in the Appendices. 17

18 Chapter 2: Demand Model Structure and Development

19 Chapter 2: Demand Model Structure and Development 2.1 Introduction This chapter sets out the development of our modelling capability to allow us to understand and test the costs and benefits of the components of the scheme as well as the overall results for the preferred package. To understand the business case for high speed rail, we employed Atkins Group Ltd to help develop a modelling and forecasting framework consisting of the following elements: PLANET Long Distance. An update of an existing model (PLANET Strategic) which was developed by the Strategic Rail Authority (SRA) for their 2001 high speed line study, and has been used for several other rail studies since. PLANET Long Distance considers the multi-modal demand (including domestic aviation) for long distance (greater than 50 miles) trips and is used to forecast HS2 demand. PLANET South. Based on an existing model, this focuses on demand for rail trips across London and the South East and has been used for analysis of schemes such as Thameslink. PLANET South allows the impact of short distance trips using long distance services and commuter services on the WCML to be understood, and is particularly important for understanding how best to use capacity on the WCML released by HS2. PLANET Midlands. A model similar to PLANET South, but focussed on rail demand in the West Midlands. Heathrow Access Model. This model, based on BAA s London Airport Surface Access Model (LASAM), forecasts the demand for passengers accessing Heathrow Airport for international flights and the potential of high speed rail (HSR) to capture this demand. As well as modelling surface access to Heathrow, this model also forecasts air transfers in which passengers fly to or from Heathrow on domestic flights in order to change onto onward international flights (interlining). Domestic (point to point) air trips are not included within this part of the model as they are captured within PLANET Long Distance. International Rail Model. A separate model has been developed to forecast the demand for international rail journeys in order to examine the case for connecting HS2 to HS With the exception of the international model, all these models were combined into a single framework to allow integrated analysis of high speed rail and appraisal of HS2 and its components. The rest of this chapter provides more detail about the structure and design of this modelling framework and the analytical approach that was used. A more complete description of the modelling approach including reports on the methodology, forecasting approach and validation of the model is published in separate documentation produced by Atkins. 19

20 HS2 Demand Model Analysis 2.2 PLANET Long Distance PLANET Long Distance forms the heart of the forecasting approach used to model high speed rail and has a number of characteristics, including: Long Distance. The model has a specific focus on long distance travel (over 50 miles) National. The model covers the whole of mainland Great Britain. However the model has been primarily designed for analysing a high speed line from London to the North and so the South West, West, Wales and Northern Scotland are less well represented. Multi-modal. The model covers domestic trips by air, rail and car. Apart from airport access (see section 2.4) coach is not included as a separate mode as it is not considered that much coach demand would want to transfer to high speed rail. This is demonstrated by coach passengers already preferring to trade slower journey times compared to rail for cheaper tickets. Segmented. The model segments people by the type of journey they are making and whether they have access to a car or not. Network based. There is a representation of the national car, rail and air networks. Transport users can therefore choose not only which mode they take, but which route best fits their preferences. All day model. Long distance demand and capacity is averaged across the whole day. Incremental model. Forecasts are based on changes to externally generated trip matrices PLANET Long Distance models the number of trips made by each mode and for each journey purpose between different areas of the country. The model divides the country into 235 geographic areas or zones, with each zone equivalent to districts or aggregations of districts. For example, the 32 boroughs of Greater London are aggregated into 7 geographical sector zones (plus Heathrow as an explicit zone). Rural Cumbria on the other hand retains its constituent districts. This is done to group zones into patterns of similar access and egress (such as Camden and Islington London Boroughs in north London), while acknowledging that east and west Cumbria may have very different access and egress, despite the far smaller population and trip activity in each district. This is shown in Figure

21 Chapter 2: Demand Model Structure and Development Figure 2.2 PLANET Long Distance Zones Box 2 - What is Generalised Journey Time? The generalised journey time or cost of travelling represents the total inconvenience of travelling between any two places expressed in common units of time or money. In the case of rail, this includes the total time taken for the journey including any time getting to and from stations or time spent waiting for a train. It also includes additional penalties if an interchange is required (in PLANET Long Distance this is equivalent to half an hour journey time penalty), for having to wait for a train, or if the train is crowded. This represents the fact that people would prefer not to change trains, and dislike waiting for a train and having to spend time on crowded trains. In addition the generalised journey time includes the financial cost of a making a journey, expressed in units of time. The conversion between time and money requires an understanding of the people put on being able to save time, a concept known as their value of time. 21

22 HS2 Demand Model Analysis To model how journeys are routed across the network, PLANET Long Distance calculates what is known as the generalised time of travelling between each pair of zones by any mode or route. Trips are then assigned to trains or routes on the network in a way which tries to minimise the generalised journey time of a trip The model can predict not only the level of demand between zones but the flows between stations and the level of demand on specific sections of the rail, air and road network. To forecast the impact of a new high speed rail line, the model calculates the change in generalised costs between pairs of zones as a result of the faster journeys offered by high speed rail. It then applies this change in costs to forecast the change in demand for each mode. This works in three concurrent stages: The change in generalised cost of travel across all modes (the composite cost ) is used to forecast the change in the total number of trips undertaken. Any new or additional trips are generally referred to as trip generation, and represent journeys that would not have been undertaken by any mode in the absence of high speed rail. The model forecasts people s preferred mode of travel using a probability based approach known as a hierarchical logit function. The logit function determines the probability of someone choosing one mode or another based on the differences in generalised costs. These mode shares are then allocated to the rail, air and road network by choosing a route with the lowest generalised journey time. This allows a degree of re-routing to occur in the light of different journey times and levels of crowding The work we commissioned delivers a significant update to the previous version of the model used by the SRA in their 2001 High Speed Rail Study. This work has included: Updating the base year trip matrices to 2008, by incorporating more recent data on rail and air demand, as well as some limited new data on roads. Updating our assumptions about the future shape of the road, rail and air networks to represent the most recent DfT assumptions on the provision of network capacity. Providing a station choice model for the London and Birmingham areas, designed to address how the accessibility of different station locations has an impact on demand. The station accessibility data is provided by Transport for London s (TfL) model of public transport access, RailPlan, and West Midlands Policy Response Integrated Strategy Model (PRISM 1 ). It should be noted that this means that the London station choice model is entirely based on public transport access costs, while the Birmingham station choice model is entirely based on car access costs. These choices reflect the data available. This means the results of these elements of the modelling require careful interpretation

23 Chapter 2: Demand Model Structure and Development In addition to updating the functionality and data in the model as described above, we also significantly changed the way the model was used compared with previous studies. We took the decision that high speed rail has essentially the same characteristics as classic rail (apart from being quicker and more reliable), and hence in our approach high speed rail is treated in exactly the same way as classic rail services. A further discussion on the reasons for this decision can be found in Chapter The changes have focused on updating demand and network data and improving model functionality. We have not sought to re-calibrate the model and the parameters which determine forecasts of mode choice and trip generation are largely taken from the previous version of the model originally developed for the 2001 SRA study. In the time available for model development, it was not possible for us conduct any new research or survey work on how travellers might be expected to respond to high speed rail With this in mind we have deliberately followed a cautious approach in our analysis and have wherever possible made assumptions that would be unlikely to overstate the demand for high speed rail. However, we do recognise that further research into some of our assumptions, and in particular the trip generation parameters, could help refine the detail of some areas of our analysis. Overall, the performance of the model has been compared against other forecasting approaches, and found to be broadly similar. 23

24 HS2 Demand Model Analysis 2.3 PLANET South and Midlands Unlike PLANET Long Distance, PLANET South and Midlands are rail only models, with relatively simple capabilities for analysing the potential for mode shift. Like the Long Distance model they include a representation of the rail network and train services, but focus on short distance trips and rail services within the South and Midlands respectively. Both of these models have recently been updated as part of work for the DfT and we have not sought to further update the models (other than to integrate them within the wider modelling framework) There are three critical differences between the structure of these models and PLANET Long Distance: The models estimates demand in the am peak only. The models calculate mode shift by an elasticity response, so there is a fixed relationship between changes in generalised journey time and demand on the railway. The models do not have an explicit mode choice model as in PLANET Long Distance. The models have a more detailed understanding of where people are travelling to and from (due to much smaller zones) The integration of PLANET South and Midlands in the PLANET Long Distance framework was important as it allows the interaction of long distance and short distance journeys to be understood. In particular, PLANET South allows better modelling of any WCML released capacity used for short distance commuting. PLANET South was also used to understand the impact of HS2 on the London Underground Network. 24

25 Chapter 2: Demand Model Structure and Development 2.4 Heathrow Access Model The final element integrated into the HS2 demand model is based on BAA s London Airport Surface Access Model (LASAM) and models the potential for HS2 to deliver improved access to Heathrow. Although based on the hierarchy, parameters and data of the LASAM model, the revised model has been developed independently and is significantly simplified to allow it to run in a spreadsheet modelling air transfers and HSR as access modes This delivers a separate mode choice model for analysing and forecasting the number of passengers accessing Heathrow airport for international flights. The model covers all surface modes, including some such as coach that are not in PLANET. These extra modes have been included because they play a more important role in accessing Heathrow than they do for other types of long distance journey. The Heathrow model also forecasts air transfers in which passengers fly to or from Heathrow in order to change onto onward international flights. Domestic (point to point) air trips are not included within this model as they are captured within PLANET Long Distance The Heathrow model is focussed on the areas of the country that are most likely to be most affected by the high speed rail networks we have considered. These areas are shown in Figure 2.4 below and include cities in the North West, North East and Scotland. It is important to note that the model does not analyse the potential market to Heathrow from areas to the west. This means for instance, that the model does not forecast the demand to Heathrow from (for example) Reading using a London Interchange Station connected to the Great Western Mainline (GWML). 25

26 HS2 Demand Model Analysis Figure HS2 Route and Areas Likely to be Affected by HS The PLANET Long Distance model automatically feeds the Heathrow spreadsheet model with information on costs of travelling by each mode to allow it to calculate revised mode shares. The demand information from the Heathrow access model (based on the costs from PLANET) is fed back into the PLANET models to allow an assessment of overall rail loadings and calculation of crowding effects as a result of all demand on HS2. 26

27 Chapter 2: Demand Model Structure and Development 2.5 International Rail Model A model for forecasting the potential demand for international rail trips was separately developed by our consultants, SKM. Data was collected from a number of existing routes in which rail and air compete in order to understand rail s mode share in relation to journey time. The model used this data to forecast the likely rail share between a number of UK and continental cities as shown in Table 2.5. This model has not been integrated into the wider HS2 framework, but is used in separate analysis. More detail on this model is provided in Chapter 9. Table Cities within the International Rail Model UK Manchester Birmingham Edinburgh Glasgow East Midlands Liverpool Europe Paris Frankfurt Amsterdam Brussels Cologne Lyon Newcastle 2.6 Additional Modelling Evidence Our modelling suite provides the level of granularity necessary to support the design of the overall scheme and provide a business case. It is designed to model the key issues, including station locations, released capacity, mode shift and the overall demand for long distance travel from Birmingham and beyond Our modelling suite is not particularly well suited to modelling localised impacts, particularly around station access and egress. Such impacts are likely to have complex interactions with short distance traffic and demand, and be affected by localised differences in the transport network. We therefore asked Transport for London (TfL) and the West Midlands transport agencies to support our work using their own more detailed models. Some early work has been undertaken using TfL s Railplan model in London and PRISM in the West Midlands, and although this work is ongoing, it has helped inform our proposals. 27

28 Chapter 3: Our Assumptions and Approach

29 Chapter 3: Our Assumptions and Approach 3.1 Introduction The HS2 demand model provides a framework for analysing the potential impacts of HS2. However the assumptions used in the modelling are key to the overall conclusions and the strength of the overall business case. There are two critical issues which will affect both forecasts and appraisal of HS2: Demand Growth The PLANET Long Distance model forecasts on an incremental basis. This means it takes forecasts of demand which are calculated outside of the model and estimates the changes to demand as a result of introducing HS2. This means the demand for HS2 is heavily dependent on the assumptions underpinning the forecasts that are input into the model (the reference case). If there is high demand for travel (across all modes) in the reference case then there is a greater potential market for high speed rail to capture, conversely if there is low demand for travel then there is a smaller market. Passenger perceptions of HSR The way in which passengers view HSR, whether they have an inherent preference for high speed trains and the way they trade off time, money and other characteristics will affect both the number of passengers and potentially the benefits they receive We have generally tried to be conservative in our treatment of these issues and have followed advice on best practice, but there is also a significant degree of uncertainty. This chapter sets out the assumptions on which we have based our analysis, and the basis for these assumptions. More detail on some of these assumptions is provided in the supporting technical documentation produced by Atkins. 3.2 Demand Growth Assumptions PLANET Long Distance forecasts the future demand for high speed rail in three stages, as summarised in the diagram below. The model is an incremental demand model which means that the model first requires demand in the future year reference case to be determined. These forecasts are largely exogenous (i.e. they are calculated outside PLANET Long Distance) and can be thought of as the growth in demand that will happen independently of HS2. This growth is driven by changes in population and employment, and in particular, people s propensity to make more frequent and longer trips as they get richer. The model then calculates how these forecasts change given a change in journey times or cost. This process is summarised in Figure

30 HS2 Demand Model Analysis Figure PLANET Long Distance Forecasting Approach 2008 data on the number of long distance road, rail and air trips Future year exogenous or background growth forecasts for road, air and rail demand provided by DfT The demand for HS2 calculated as a change to future year background growth Base Year demand data The starting point for forecasting future demand is observations on how long distance trips are currently made and distributed in the 2008 base year. Data has been collected showing the number of trips over 50 miles made between each pair of zones in the model split by mode and journey purpose (leisure, commuting and business), with some additional breakdowns of whether a car is available to undertake the trip. The data has been collated from a number of different sources: Data on domestic air trips has been extracted from Civil Aviation Authority survey data. This data is considered robust and is consistent with data used by the Department for Transport s aviation model. Rail trips have been derived from a combination of the LENNON ticket sales database and the National Rail Travel Survey (NRTS). NRTS has been used to understand how people access and egress stations, and to infill areas where the ticket sales database is known to be weak. Unfortunately there is no robust national dataset providing the origins and destinations of long distance car trips. Data on car trip matrices has therefore been derived from regional Multi-Modal Studies, with some updates using the Highway s Agency North of Thames Highway Model and the West Midlands PRISM model. While this remains one of the best available sources of car trip data on a national basis, the accuracy of the data still remains much weaker than that for rail or air, and considerable uncertainty remains about the accuracy of the demand matrix for this mode. Demand Growth on Air and Road Networks The base year demand matrices for road and air are then uplifted to represent the expected growth that will occur in each of these modes. This exogenous growth is independent of any subsequent changes that are made to the rail network such as high speed rail. Growth in road and air traffic has been based on the Department for Transport s most recently published forecasts; the road forecasts are based on the 2008 Road Transport Forecasts 2 and the air forecasts are based on the 2009 Air Passenger Demand and CO2 forecasts. 3 2 DfT 2008 Road Transport Forecasts DfT 2009 Air Passenger Demand and CO2 forecasts 30

31 Chapter 3: Our Assumptions and Approach These air and road traffic forecasts have been produced by the National Transport Model (NTM) and air traffic model (SPASM), and the underlying assumptions used by these models and PLANET are generally consistent with one another. For instance all the models are based on the same TEMPRO planning data. The forecasts also include assumptions about the future road and air networks. The NTM assumes that investment in the road network continues at current trends, while the air traffic model assumes that Heathrow has a third runway. These assumptions are described in the supporting documents produced by Atkins. Demand Growth on Rail Network The exogenous rail growth has been calculated using the standard industry and Government recommended approach in WebTAG known as PDFH (Passenger Demand Forecasting Handbook). This methodology uses a set of fixed relationships between demand and various drivers such as fares, employment, GDP/GVA and population which have been derived from econometric analysis of past rail growth. In keeping with WebTAG the relationship between rail growth and fare is taken from PDFH edition 4.0, whilst all other relationships come from edition There are, however, a number of issues with this approach: Unlike the road or air forecasts, PDFH uses fixed income elasticities. This means that for every 1% growth in GDP there is a constant percentage increase in rail demand. Using this approach implies rail demand will grow indefinitely (in line with GDP). There is no slowing of growth, market maturity or saturation effect. Over an appraisal period of 60 years this can have a very strong influence on the appraisal results. To proxy for market maturity and the long term lack of certainty in the forecasting methodology, the Department recommends capping demand growth at a future date after scheme opening. The cap is usually applied at 2026, reflecting 10 or more years of demand growth after scheme opening. However as HS2 will not be opening until the end of 2025 we have decided to cap demand at PDFH v4.1 income elasticities have a distance term and hence can therefore become very high for very long distance trips. Following advice from the Department PDFH elasticities have been capped so that even for the very longest distance flows they are limited. For example PDFH v4.1 suggests rail demand between Aberdeen to London will grow by 3.7% for every 1% increase in GDP (elasticity of 3.7). Following DfT advice this has been capped at 2.8% growth for every 1% increase in GDP (an elasticity of 2.8) These elasticities are applied to estimates of population and employment that have been supplied by DfT s TEMPRO 4 model. All rail fares are assumed to grow at RPI+1 until 2033, while GDP forecasts are in line with the latest Treasury forecasts, but not the current DfT WebTAG guidance. We anticipate DfT will update its forecasts and guidance in due course, but for now it leads to a slight inconsistency, with DfT projections (including those used by HS2 to project air and car demand) using higher GDP projections

32 HS2 Demand Model Analysis The demand model uses these exogenous forecasts as the basis for projecting the incremental impact of HS2. It is also clear that these assumptions are important in generating the strength of the business case. For this reason further sensitivity tests have been undertaken on the impact of different levels of demand. These results are reported in Appendix Passenger Preferences and the Treatment of HSR in the Demand Model Demand models are an attempt to forecast the preferences and behaviour of the travelling public, given a change in the transport network. The choices people make are based on a wide variety of factors, and individuals preferences will vary compared to the average transport user. Indeed their preference may also vary depending on circumstance the importance of time and reliability when travelling to catch a flight will be very different to a day trip to the seaside Most transport models which explicitly forecast mode choice (e.g. PLANET Long Distance) are probability based models. 5 They calculate the probability someone will use a particular mode to undertake a trip. So even if rail is faster, cheaper or more reliable for a particular trip, it does not mean everyone will use rail. Put another way the model captures both the things we can identify and understand in choices, but also allows for variations that we cannot directly observe. The model is therefore calculating two different things: The generalised cost of a mode given average preferences. The variation in individuals tastes and how this affects the distribution of choices This works well for determining people s choices between existing modes car, rail, air. In this case we can observe people s existing behaviour how they trade off time or the inherent attractiveness of one mode over another on the basis of the actual choices they are seen to make, as well as by asking people directly through surveys. However, we cannot observe their behaviour for high speed rail, since it does not currently exist in this country (or has not been in place for long enough) so we can only ask people what they think they might do Past surveys have suggested the way people might behave on high speed rail is different to the way they treat classic rail. The surveys used to develop the original PLANET model, used by the SRA in 2001 for example suggested passengers placed a value on high speed rail over and above the time savings compared to classic rail. 5 These are models with techniques such as the hierarchical logit model used in PLANET Long Distance, rather than elasticity based models such as PLANET South and Midlands. 32

33 Chapter 3: Our Assumptions and Approach There is a variety of reasons why people may prefer travelling by high speed rail as opposed to using classic rail or another mode. These include: High speed rail offers a faster journey. High speed trains are more reliable. High speed trains are more luxurious. The experience of travel on high speed rail is somehow more enjoyable, with for instance better ticketing, pre-booked seats, better stations etc. There are fundamental differences between the characteristics of high speed rail users and classic rail users, in particular the way in which they value time savings A review of the evidence from the SRA survey work suggested that passengers preferences could have been overstated, with the value of reliability a particular issue as the study took place shortly after the Hatfield incident when rail reliability was exceptionally low. We have also taken a conservative view that the quality of rolling stock and stations should not differentiate high speed rail, as in the future the differences between the perceived quality of high speed and classic rail stations and trains could be very small. Neither is there reason to believe that in the absence of premium fares (see section 3.5) the average high speed rail passenger would be somehow different from the average long distance passenger on the classic rail network. In particular there is no reason to believe that the average high speed rail passenger will value time savings more highly on high speed rail We therefore concluded that in our analysis of high speed rail we would only consider the impact of time savings and reliability on demand. As a result high speed and classic rail passengers are treated in exactly the same way within the PLANET Long Distance model. Whilst reliability benefits could have been modelled through adjusting mode choice parameters in PLANET Long Distance, it was felt more appropriate and transparent to model this by adjusting journey times (see section 3.4). This means HSR is not treated as a new mode and there is no mode choice hierarchy between classic rail and HSR. Similarly there is no difference in peoples perceived preferences for HSR compared to classic rail and users value of time remains the same whether they travel on classic or high speed rail. 33

34 HS2 Demand Model Analysis 3.4 Measuring Reliability Impacts of HSR Capturing reliability impacts in our modelling creates a particular challenge. Other schemes (at a detailed level of design) might use explicit models of rail performance which vary according the precise detail of the scheme, the capacity and demand on the local railway network. Such modelling is not appropriate for the stage of design of HS However it is clear from international experience that high speed lines can offer very high levels of reliability compared to a mixed use railway such as the WCML, and that this can have a significant impact on demand. The design of the line has also built in costs to ensure the reliability of the line for example timetabling has been undertaken assuming trains run slower than the maximum line speed to allow for trains to catch up most small delays. As we measure the disbenefits of these increased journey times, it is therefore important that the off-setting benefits of reliability are also understood Our approach to modelling reliability is fairly simplistic and involves making adjustments to the journey times as a proxy for changes in reliability. Our approach considers the potential improvement in reliability that HS2 can deliver by examining one measure of reliability average minutes lateness (AML). Improvements in AML as a result of HS2 are then converted into an equivalent journey time saving based on evidence in PDFH and WebTAG, which suggests that passengers value 1 minute average lateness as equivalent to 3 minutes of journey time. This artificial reduction in journey time is then input into the model to forecast the change in demand due to reliability improvements. Day One Central Case We have used DfT s Network Modelling Framework 6 to forecast the average delay expected on the WCML in 2020 without high speed rail. This forecasts that performance on the WCML will mean 91% of trains arriving within 10mins of their scheduled time with an AML of 2-5mins. Consistent with international practice, HS2 is expected to operate at much higher levels of reliability than can be achieved on the classic network. For dedicated services on the high speed line the AML is expected to be less than half a minute HS2 hybrid services running on both the high speed and classic network will have some benefit from running partly on a more reliable network, but will still experience delay when running on the classic line. There is greater uncertainty about the impact on reliability of these journeys since: We have not currently used evidence on where trains are delayed whether this is on the section to Lichfield which HS2 bypasses, or sections further to the north. There are likely to be compound effects a short delay on a train leaving London may mean it misses its path further along the line, resulting in further delays. Hence small improvements in reliability on one section of a line could have larger improvements in overall reliability

35 Chapter 3: Our Assumptions and Approach The impact of HS2 may be complex. The approach to timetabling on HS2 may allow for fast running and further catch-up time. However capacity constraints may mean that a train which misses its slot on HS2 has a greater impact on the reliability of the line We have assumed that the reliability of HS2 hybrid services is proportional to the distance run on HS2. Table 3.4a below shows the expected performance and equivalent journey time reduction for services on HS2. This means that the modelled journey time between London and Birmingham is reduced from 49 minutes to 41 minutes, with the demand forecasts based on this reduced journey time. A sensitivity test on the impact of these assumptions is included in Appendix 2. Table 3.4a Reliability Benefits of HS2 HS2 Service Group AML Classic Rail Forecast AML with HS2 Change in AML Equivalent Journey Time Reduction (i.e. 3 times AML) London - Birmingham London - Preston London Manchester London Liverpool London - Scotland Day One Extension to Leeds and Manchester If the Day One high speed network were extended from the West Midlands to serve Manchester and/or the East Midlands, Sheffield and Leeds then journeys to these destinations would also benefit from improved reliability. The impact this has on the journey time of each link of the network is shown in Table 3.4b. It is assumed that the time savings are distributed across the network in a manner roughly proportional to distance. Table 3.4b Reliability Benefits of HS2 extended to Leeds and Manchester HS2 Service Group AML Classic Rail AML HS2 Change in AML London - East Midlands/ Sheffield Equivalent Journey Time Reduction London - Leeds London - Birmingham London - Manchester London - Liverpool London - Scotland

36 HS2 Demand Model Analysis 3.5 Premium Fares Model Section 3.4 of this chapter outlines our approach to modelling the preference of HSR passengers compared with classic rail. This approach considers the way the average passenger trades-off time, money and other costs of travel. It acknowledges that there will be a variation in these preferences across individuals by working out the probability of any journey being undertaken on a particular mode. This works well so long as the variation in preferences is essentially random, which is likely as long as the characteristics of high speed rail and classic rail are the same. However, if the scheme results in the selection of a group of people with a particular set of characteristics (for example if the people who would tend to use a scheme are of above or below average income) this assumption may not be valid Premium fares are an example of this. If a premium fare were charged on HS2, passengers would have to trade-off time and money whether to pay more money and get a time saving or stay on classic rail and pay less money but incur a slower journey. Those with a low value of time will tend to use classic rail since they do not value the time saving sufficiently to warrant paying the extra fare. This is not a random variation, rather it reflects the different characteristics of passengers. With a premium fare, by definition, the average high speed rail user will value time savings more highly than the average classic rail user Ideally we would capture and model this variation, but the design of our base model does not allow this, since the value of time of both high speed and classic rail users is assumed to be equal. In addition to this, our decision to treat HSR the same as classic rail meant that the existing model structure prevented analysis of fare premiums over and above those charged on classic rail the two fares are the same for the purposes of the model For these reasons we have developed an alternative modelling approach for modelling premium fares on high speed rail using PLANET Long Distance. It still assumes an individual sees high speed rail as the same type of mode as classic rail, but rather than assuming that the value of time of rail users is a single average, the approach now assumes there is a range of individuals each with different values of time. In this approach the introduction of a premium fare leads to those with low values of time choosing classic rail and those with high values of time choosing high speed rail The distribution of value of time is drawn from evidence from the National Rail Travel Survey, 7 with income used as a proxy for value of time. The resulting model has allowed us to model the impact of premium fares. However it has not been applied to analysis of our central case since this does not include premium fares. The Distributed Value of Time model is not appropriate in this case since it will simply assign all rail users undertaking journeys served by HS2 onto HS2 trains overstating the likely shift from rail. It was therefore only used for tests of premium fares

37 Chapter 3: Our Assumptions and Approach We report the results of sensitivity tests on premium fares in Appendix 2. Our investigations have so far identified that, while there may be some scope for premium fares on HS2 to improve affordability, these fares structures are likely to be complex and need more assessment than is possible in the time available. For this reason our central case does not include premium fares, and so does not apply the Distributed Value of Time model. However this is an issue that could be investigated in more detail in the future. 3.6 Applying the HS2 Service Specification The service pattern that we have modelled is included in the HS2 report and summarised in Figure 3.6. It represents an indicative outline of the possible service specification for the purposes of the demand model. Figure 3.6 HS2 Service Specification Running on HS2 Additional peak hour service Running on classic line HS2 station Existing classic rail station The development of the service specification is indicative to allow the development of the business case. It is a credible service plan tested against the capacity of HS2 and the WCML on which some classic compatible trains would run on. It also includes an assessment of the potential for released capacity. However it has not been subject to any degree of timetable validation, and there is the potential for further iterations as the project develops. Any such changes may change both the costs and benefits in this report. 37

38 HS2 Demand Model Analysis The application of this specification is limited slightly by the nature of PLANET Long Distance. In particular PLANET Long Distance is an all day model, working on average capacity and demand across the whole day. However the crowding function takes account of the variation of demand across the day. For example, an average load factor of 60% across the day would imply crowding during the peaks. The model therefore applies some crowding penalty even though on average trains are not crowded The service specification assumes 400m trains will run between Birmingham and London during the peak hours. However simply adding this additional capacity would be assumed to be spread across the day, and would potentially over-state the level of crowding. For this reason we have assumed (for the purposes of modelling only) that all trains to Birmingham are 400m trains throughout the day This will mean that average load factors on Birmingham trains will be slightly understated, but this is likely to provide a more representative picture of the crowding impacts on HS2, with capacity targeted over the most crowded times. Yield management would also help to spread demand and reduce crowding. 3.7 Economic Appraisal We have broadly followed DfT s transport appraisal guidance (WebTAG). The results presented in this report are all present values, discounted over 60 years (unless otherwise stated). We have deviated from this guidance in three areas. Firstly our reference year is 2009, and not This is a presentational change, and all present value costs and benefits can be converted to 2002 using a constant factor to allow comparison with other schemes. These adjustments do not change the BCRs. Secondly we have considered the evidence on Wider Economic Benefits. We have applied DfT s draft guidance on WEBs, however we have also looked at whether there are further impacts that HS2 may generate that are not captured in this methodology. This is discussed in more detail in Chapter 10. Finally, when considering the benefits to transport users under scenarios with premium fares we have applied different values of time to those outlined in WebTAG. In this circumstance the equity weighted values that are used by WebTAG can cause misleading results If premium fares were charged on HS2, users would have to trade-off the value of the time saving against the additional cost of the fare. Users with a high value of time will be better off paying the premium and gaining the time saving. However applying an equity weighted value of time could give the opposite impression (Box 3 provides an example of this). 38

39 Chapter 3: Our Assumptions and Approach Box 3: How to Appraise Time Savings in the Presence of Premium Fares The introduction of HSR could represent an additional route choice over the existing WCML services. In this case, those that shift will value the time saving by enough to outweigh any additional fare costs. In other words their welfare will improve. However using a standard value of time may suggest the opposite. Take the following example: A high speed line saves 30 minutes and the fare is 25 higher Person A is travelling for business purposes by rail and has a value of time of 70 per hour, so will switch to the high speed line and be 10 better off However using the WebTAG standard value of per hour, it appears that this person is 6.52 worse off So in this case a WebTAG consistent appraisal would suggest HSR has a disbenefit to transport users (when in fact users have benefitted) All of these changes are necessary for analysis of specific issues relating to HS2 and the questions we have addressed. However the core analysis and conclusions are all based on appraisal results that are consistent with existing Government guidance. 39

40 Chapter 4: Central London Station Location

41 Chapter 4: Central London Station Location 4.1 Introduction This chapter sets out the analysis that helped us choose the preferred location for a terminal station in London. Our analysis focussed on resolving three main issues: The basic accessibility of different station locations, in particular the differences in demand between inner and outer London stations. The impact of HS2 on the number of people using the preferred station location, both for classic and the high speed rail. The impact of HS2 on the local transport network dispersing passengers to and from the preferred station location Our modelling and analysis draws from data within Railplan to estimate the patterns of demand across London where typical day trips start and finish within London and the accessibility of potential HS2 stations when using public transport (as the main access mode). 4.2 Choosing a London Station Location We took an early decision that termini stations should be located in Central London (i.e. within Zone 1 on the London Underground Network). This decision was informed by examining the size of the markets for long distance trips starting or ending in London. This showed that: Approximately half of long distance trips from London originate from central London. This market was also the focus of rail demand, and therefore particularly important for HS2. The average access time/cost for passengers in London to reach an Outer London station using public transport would be significantly longer than most central London stations. Whilst some (in the vicinity of the station) would gain, many would lose. On average this would largely off-set any gains from faster journeys on high speed rail Table 4.2a below sets out the number of trips from London to the West Midlands, by origin in Over half of all trips (and 90% of rail trips) start within central London. This represents a core market for high speed rail, particularly as we would expect to capture the majority of rail trips (in the absence of premium fares). Trips that start in Outer London are dominated by car trips. Whilst this reflects an opportunity for HS2 to deliver mode shift, it also reflects the diverse range of origins and destinations. Car is likely to be more attractive for trips which start or finish a significant distance from a train station at either end. 41

42 HS2 Demand Model Analysis Table 4.2a Annual Trips between London and Birmingham (2 way) 2008 Annual Demand Central London Outer London Rail 6,570, ,000 Highway 1,980,000 5,290,000 Total 8,550,000 6,030, The importance of city centre to city centre travel in the rail market suggested it would be important for HS2 to serve this core market effectively, since it was likely that the bulk of demand on HS2 would be drawn from existing rail trips. While the market to and from outer London should not be ignored, our analysis suggested any terminus station should provide good access to the existing rail market from central London. A central London station would tend to provide good access to this market. However, it was unclear whether a terminus outside of central London would achieve this We considered evidence from TfL s RailPlan model on the accessibility of different station locations to assess how well each potential station might serve this core market. Of the non central station locations considered by HS2, and along the line of route to Birmingham, Old Oak Common provides the greatest accessibility, particularly with the potential for additional Crossrail and GWML connectivity. Hence it appears to be the best potential candidate for a terminus if HS2 were limited to non Central London stations only. Despite the potential for enhanced Crossrail services at Old Oak Common, the station would be significantly less accessible than a central London terminus. For the average trip using public transport to access HS2 and starting in London, the cost penalty for going to Old Oak Common compared to Euston is equivalent to almost a 30 minute time penalty This time penalty represents a significant additional cost on a journey from Inner London. Table 4.2b below considers a simplified journey from inner London to Birmingham to demonstrate the impact of the difference in access costs between Euston and Old Oak Common for the average passenger. The table shows that a terminus station at Old Oak Common would reduce the benefits of HS2 per passenger by over two thirds compared to a station at Euston, and as a result was likely to severely limit demand and economic benefits. This does not consider the potential for access via car and taxi. This may be more attractive for a station outside of central London. Table 4.2b - Generalised Journey Time of a Trip from Inner London to Birmingham Mode Access Penalty Rail Journey Time Total Generalised Journey Time Existing Rail HS2: Euston HS2: Old Oak Common

43 Chapter 4: Central London Station Location However, within this average there are some passengers in West London who would see significant gains; it is those in the south and north of London who would find accessing a terminus at Old Oak Common more difficult. Figure 4.2 shows that large areas of London would have better access to Old Oak Common than to a Euston station. However Euston has better access for the core markets within central and inner London thus has better average accessibility for this core market. Figure 4.2: Map Showing Areas Best Served by Stations at Old Oak Common and Euston when Using Public Transport This suggests a station outside Central London may still have a role as an interchange, allowing even better overall access for passengers travelling to and from London. However, as a terminus it is unlikely to be attractive. On this basis locations outside of Central London were not pursued in detail as terminus stations, whilst the most accessible Central London stations remained terminus options for HS2. 43

44 HS2 Demand Model Analysis 4.3 Analysis of Euston For reasons outlined in the Summary Report, we recommend that Euston is part of the preferred scheme. In the main the decision between central London stations was driven by environmental, cost and engineering issues since the demand at most of the potential Central London stations sites is likely to be similar. The impact of HS2 at Euston has been carefully analysed as described in Table 4.3a below. Table 4.3a Summary of Daily Demand at Euston Daily Demand 2008 Base year 2033 reference year Do Minimum 2033 without Old Oak Common 2033 with Old Oak Common All day: National Rail at Euston AM peak 3 hours using National Rail at Euston Expected to use LUL AM peak 3 hours 52, , , ,000 22,000 39,000 64,000 45,000 14,000 24,000 39,000 28,000 Source: All Day demand from PLANET Long Distance. This represents all rail trips (both long and short distance) made on long distance trains. It therefore excludes short distance trips made on short distance services. Am peak 3 hours demand from PLANET South. This includes all rail trips (both long and short distance) made on all services (both long and short distance). LUL demand is 62% of PLANET South data, as described in the footnote and is therefore includes the demand from all rail trips both long and short distance The PLANET models indicate that in ,000 national rail passengers arrived or departed Euston Main Line Station each weekday on long distance services. In the three-hour am peak from 7 to 10 am around 22,000 passengers arrived or departed on both long distance and short distance services. From survey data, 8 we know that in the peak period 60-70% of Euston mainline passengers use the underground, which would correspond to 14,000 passengers While Euston Underground station is not currently the most heavily used London Underground station, many trains passing through the station are still very crowded during the three-hour a.m. peak. We have used the HS2 demand model (PLANET South) to look at the impact of HS2 on the Underground. This model tends to overestimate the number of passengers using the Underground, in part because it does not include taxis as a mode of dispersal. We are working with TfL to conduct further detailed modelling of the impacts of HS2 around Euston, however for now PLANET South provides a reasonable view of the impacts on the Underground network London Area Transport survey (LATS) and 2008 RODS data indicates across the whole day 50% of Euston Mainline passengers use the Underground and in the morning peak 62%. PLANET South indicates a much higher proportion of passengers. However PLANET South tends to overestimate the number of passengers using the underground, in part because it does not include taxis as a mode of dispersal. 44

45 Chapter 4: Central London Station Location PLANET South suggests the most heavily crowded trains are southbound on Northern and Victoria lines where even now there are currently more than 2 passengers for every seat. The average loading on all London Underground services going through Euston in the 3 hour morning peak is 138% as shown in Table 4.3b below. Table 4.3b Average Loadings on all LUL Services to and from Euston Underground Station in the 7-10am Morning Peak Average LUL Load Factor (Volume/ Seats) 7 10 am peak 2008 Without HS Without HS With HS2 without OOC 2033 With HS2 with OOC 138% 185% 194% 191% This situation will continue and get worse, even without HS2. Whilst capacity on the Northern and Victoria lines is expected to increase by around 20% (an extra 40,000 seats at Euston during the a.m. peak) by 2018, demand on the Underground will have grown by 34% by 2021 and 61% by Thus in the absence of further capacity enhancements, crowding on the Underground is forecast to increase by This increase is driven by several factors, many of which are related to growth in London s economy (which drives growth in use of the Underground network by London passengers). However, one further element is that more people will want to travel to and from national rail stations due to the high growth in national rail demand. At Euston, the number of passengers arriving or departing the station even without HS2 is forecast to grow by 60% by 2021 and 143% by This means that by 2033, even without HS2 there will be around 10,000 additional national rail passengers using the underground network at Euston HS2 will add further demand. Our central case which includes an interchange at Old Oak Common - would result in almost 140,000 passengers arriving at or departing from Euston each day on long distance services an increase of 14,000 passengers compared to the case without HS2. These passengers are made up of almost 100,000 passengers using HS2 and around 40,000 using residual long distance classic rail services. This is equivalent to around 6,000 extra passengers during the course of the 3 hour morning peak, of which 65% are likely to use the Underground network. This would represent an increase of just 3% in the number of passengers on Underground trains at Euston and increase the average load on a train to 1.91 passengers per seat (from 1.85) as shown in Table 4.3b Overall our analysis suggests that despite the major investment provided by the PPP, by 2033 there will be increased crowding on Underground services through Euston and it is likely further investment may be needed to manage this. The addition of HS2 will put some further pressure on the Underground network, but the impact is relatively small compared to the total numbers of other underground passengers travelling through Euston. Our modelling suggests crowding on services through Euston Underground Station will increase by 3% as a result of HS2. 45

46 Chapter 5: London Interchange Station Location

47 Chapter 5: London Interchange Station Location 5.1 Introduction This section of the report outlines the analysis that underpins our recommendations for a London interchange station. It starts by setting out the options that were considered for modelling, before moving on to consider the implications of a station at these locations for the core markets that an interchange would serve. We conclude by summarising the key points behind our decision to include Old Oak Common in the core HS2 scheme. 5.2 Options for a London Interchange Station We started from a list of 11 potential station locations running approximately along the line of the GWML between approximately Old Oak Common in the east, through to Heathrow in the west. Following an assessment of the environmental and engineering implications of these stations 7 options were sifted out. The remaining options were considered in more detail through modelling work. These were: Old Oak Common. Heathrow Terminal 5. Heathrow Terminal 6. Iver We further simplified the modelling of the three Heathrow options (terminals 5 and 6, and Iver) using a single modelling construct. This assumed the best elements of all of these stations, including: Direct (cross platform) connectivity with GWML. Connectivity with Heathrow airport terminals equivalent to that offered by a station at the Central Terminal Area. Connections to Crossrail, Heathrow Express and the Piccadilly line via the Central Terminal Area, providing dispersal options to London. A parkway station with direct access to the M25 for HS2 passengers travelling to and from locations outside of London This provides a best case for Heathrow, and allows us to consider the potential size of each component of demand. In practice no single Heathrow station option can provide all of these elements: A station at Heathrow terminal 5 would provide connectivity to the airport, to London via a connection with Crossrail, Heathrow Express and the Piccadilly line, and parkway access. However it would not have a connection to the GWML. 47

48 HS2 Demand Model Analysis A station at Terminal 6 is likely to provide connections to the airport, as well as London via Crossrail and Heathrow Express. It is unlikely to have a connection to the Piccadilly line, nor have direct access to GWML or a parkway. A station at Iver would have connections to GWML, and potentially to a parkway. However whilst a link to the airport could be established it is unlikely to have connectivity equivalent to a station on the airport. Similarly this is unlikely to have connections to the Piccadilly line or Heathrow Express, and only limited Crossrail services In addition to these locations, there were three different ways a Heathrow station could be served a through, a loop and a spur station (see Figure 5.2). Each of these options has different implications for the capacity of HS2, and the journey times for HS2 passengers particularly those travelling to London. Figure 5.2 Options for Serving Heathrow A loop allowing a through service via Heathrow A spur for trains accessing Heathrow The main route via Heathrow A station at or near Heathrow 48

49 Chapter 5: London Interchange Station Location In the case of a spur solution, one complete train path into London would be lost by every train serving and terminating at Heathrow via the spur. Since the majority of passengers are travelling to London, a spur option is unattractive, as the value of the capacity foregone, threatening for instance the ability to provide a reasonable service to Birmingham or to run service between London and Leeds via the East Midlands and Sheffield as part of a wider network, would significantly exceed the capital cost saving of up to 1.5 bn. A spur option was therefore not considered further With a loop option, not all trains would stop at Heathrow. The assessment of HS2 s engineers is that with optimised service patterns around the loop it would be possible to deliver this with no impact on the capacity of the line. With a through station, a choice would need to be made on stopping patterns: If all trains stop at the through station, there will be no impact on the capacity of the line. There will, however, be significant time penalties for those passengers (the majority) travelling beyond the through station. In the case of selective stopping, there will be an impact on capacity since a train slowing down to stop at a station will have an impact on any train behind that is running at full speed (and similarly on a further path when accelerating away from the station). This could reduce the capacity of the line by up to one train for each train stopping at the station. It would, however, permit a service pattern in which not all HS2 passengers suffered the time penalty of stopping at Heathrow (though this would also reduce the number of services for those who do wish to use a Heathrow station) For the purposes of this analysis, we have focused on a through station at Heathrow where all HS2 trains stop as a comparison to a station at Old Oak Common. We are currently conducting further analysis on Heathrow stations, including further tests of a loop stations and through stations with selective stopping. We will publish this analysis in due course. However for the purposes of this paper we limit the comparison of a through and loop station to a strategic comparison of the alternatives. 5.3 The Potential Markets for a London Interchange Station Reflecting our remit, we have assumed the two main objectives for a London interchange would be to: Provide good access for HS2 passengers to London, whilst relieving pressure at Euston. Provide access to Heathrow airport for HS2 passengers In addition to this, for the purposes of appraisal, we have to consider the benefits of connections to the GWML, and to the road network that facilitate journeys to outside Greater London. The following sections take each of these markets in turn, considering the market potential as well as the implications of the Old Oak Common and Heathrow stations. 49

50 HS2 Demand Model Analysis Improving Access to London The largest market that is forecast to use HS2 is people travelling to and from locations within the Greater London area. London already dominates the rail market accounting for almost 80% of trips by rail between the wider south east and the West Midlands, North West and Scotland. We forecast this trend to continue, with over 100,000 HS2 passengers travelling to and from London each day in In our central case around 80% of passengers on HS2 are travelling to and from locations in Greater London An interchange station would have different impacts on these passengers depending on where they are travelling to or from. Some would see improved access times as a result of the interchange station, particularly those travelling to and from West London. However those who do not use the interchange station will experience journeys that are 4 minutes longer as a result of stopping at Old Oak Common and 9 minutes longer at Heathrow reflecting the longer route needed to serve a Heathrow station. Table 5.3a - Number of HS2 Passengers Travelling to and from Greater London at Different HS2 Station Locations Daily Demand Interchange Station Euston Total HS2 with no London Interchange 0 113, ,000 HS2 with OOC 31,000 84, ,000 HS2 with LHR Through 14,000 79,000 93,000 Note: This only includes HS2 trips whose ultimate origin or destination is in Greater London Table 5.3a shows how many passengers using HS2 are accessing Greater London, and which HS2 station these passengers use. It suggests that a station at Old Oak Common would increase the total number of passengers travelling to and from London on HS2 compared to having no interchange. This means that the benefits of improved accessibility would more than outweigh the costs of slower journeys for those travelling on to Euston A Heathrow station on the other hand would reduce the number of passengers on HS2 travelling to and from London. This reflects the additional time penalties imposed on passengers travelling to Euston reducing demand at the Euston station as well as the longer journey times on public transport between a Heathrow station and many locations in Central London. Relieving Dispersal at Euston Chapter 4 has outlined the pressures on the Underground network at Euston, both with and without HS2. It also outlines the impact of HS2 at Euston in our central case including Old Oak Common. We consider here further the role of the interchange in relieving pressure at Euston. 50

51 Chapter 5: London Interchange Station Location Table 5.3b - Number of HS2 passengers using Euston Station Daily Demand HS2 Passenger arriving and departing Euston HS2 with no London Interchange 134,000 HS2 with OOC 95,000 HS2 with LHR Through 88,000 Note: This data represents all HS2 trips passing through Euston Table 5.3b shows the number of HS2 passengers arriving at and departing from Euston each day under each scenario. The difference with Table 5.3a is that this now includes trips which may start or end outside London, but travel via Euston. In addition to the HS2 passengers using Euston, there are approximately 40-45,000 passengers on the residual long distance classic rail services using Euston In our central case (including Old Oak Common) this represents an increase of 14,000 passengers through the day compared to no HS2 (6,000 passengers during the three morning peak hours). The net effect of this would be to increase passengers and crowding on London Underground lines running through Euston by around 3% during the morning peak Without a London interchange station, the number of passengers at Euston and on the Underground network would be increased. Compared to our central case (which includes Old Oak Common), there would an additional 35,000-40,000 HS2 passengers per day using Euston and an additional 11,000 using the underground in the am three hour peak. Overall this would almost quadruple the impact of HS2 on the underground network at Euston. However even this significant growth would only represent an increase in the level of crowding on the Underground at Euston of just 5%, since Euston passengers make up a relatively small proportion of the total number of passengers on the Underground network at this point A station at Heathrow would serve to reduce the number of passengers arriving or departing at Euston up to 46,000 passengers per day. However it would do so almost entirely as a result of longer journey times discouraging passengers using HS2 to travel to and from London, rather than improving the dispersal of London passengers. Access to Heathrow The potential market for trips on HS2 accessing Heathrow comes from three sources: Surface access trips to and from Heathrow to access international flights; Air trips to access international flights (interlining); Potential for Heathrow to gain market share from competitor airports as a result of improved accessibility. 51

52 HS2 Demand Model Analysis This does not include domestic air passengers as these people are treated as either accessing London, or other locations in the UK (both of which are considered separately) Our modelling is designed to cover the market potential of a full high speed network, serving both the North East and North West, as well as Scotland. Our data suggests that there are around 8,000 surface access trips per day in 2007/8 (2.5m trips per year) to and from Heathrow that might be captured by such a network. These trips start and finish from an area north of Birmingham, including Manchester and Glasgow, but also places like Newcastle and Edinburgh In addition to this there are around 4,000 interlining or air transfer trips made per day (1.2m trips per year) by air between Heathrow and Glasgow and Manchester airports in A further 3,000 interlining trips per day (800,000 trips per year) come from Newcastle and Edinburgh which would be covered by a wider network. Trips from Glasgow and Manchester airports form part of the potential market for access to Heathrow with just HS2, while Newcastle and Edinburgh more likely to be captured by a wider high speed network A further 5,000 trips per day start or finish in an area in the region of an intermediate station. However these are unlikely to be a potential market given that the core HS2 proposition does not include an intermediate station This suggests that based on 2007/8 data, the market potential for existing trips that access Heathrow from the areas served by a full high speed network is around 15,000 trips per day (4.5m trips per year). This compares to around 145,000 trips per day forecast to use HS2 to and from London in 2033, and 220,000 that would use a full High Speed Network (see chapter 11) In practice HS2 will not be able to capture all of this potential demand. The service on the first leg of HS2 will only provide journey time benefits to the North West and Glasgow. A large area of the North East and Scotland which is included in the market potential above would not benefit from the scheme. As a result the number of passengers that could use HS2 to travel to and from Heathrow is likely to be much lower Our model suggests a station at Heathrow would deliver the greatest demand for access to Heathrow, with around 2,000 passengers per day using HS2 to access the airport for international flights. This means that even a station at Heathrow which is deliberately modelled to maximise the attractiveness for airport passengers would represent less than 2% of the traffic on HS This modelling assumes that HS2 will not increase the total number of passengers accessing Heathrow. It is possible that by boosting accessibility to Heathrow, HS2 will make Heathrow more competitive with other UK and European airports and therefore change the distribution or number of passengers to the airport. It is difficult to assess the size of the potential for this shift. BAA in its submission to HS2 suggested there were around 13,000 trips per day (4m trips per year) from UK regional airports to European airports for onward connections to international flights. This is a potential market that could transfer to Heathrow if HS2 significantly improved access to the airport. 52

53 Chapter 5: London Interchange Station Location In addition, data from the CAA suggests that the market from the West Midlands and beyond for Gatwick and Stansted combined is around 12,000 trips per day (3.7m trips per year) If we include both of these, then the potential market to Heathrow would amount to around 43,000 trips per day (12.8m trips per year). Even if HS2 were to capture all of these trips, it would represent around 20% of trips on HS2 comparable to the number of passengers accessing UK destinations outside London, but only around one third of the number of passengers travelling to and from London HS2 s core market. In practice it is unlikely HS2 would deliver such a significant change, since it does not directly serve large parts of the markets considered (e.g. Newcastle and the North East). A wider high speed network may capture a higher proportion of this market, but even then it would be heavily dependent on the competitive responses of airlines and airport operators both within the UK and Europe. Trips to and from Locations Outside of London HS2 passengers would have a variety of different origins and destinations. We have already seen that the majority of passengers would travel to and from the Greater London area. However a significant number (almost 20%) would be travelling to and from locations outside of London. An interchange station would enhance access for these passengers. For example someone travelling between Reading and Manchester would have a journey of just under three and a half hours. With HS2 and an Old Oak Common interchange this could fall to just over two hours with one interchange. This is likely to be a more attractive proposition, particularly in the absence of premium fares However the design of the HS2 model raises two issues related to the size of this market. In particular it assumes all fares between different places in the country are the same regardless of the route taken. In practice the fare paid by passengers from places like Bristol and the South West, using the GWML and then HS2 to reach Manchester and beyond is likely to be higher than the equivalent Cross County trip. This difference in fare would act to discourage passengers from using HS2, but is not taken into account by our modelling. There is also significant crowding on Cross County routes by 2033, which increases the propensity of passengers to switch to using HS As a result the flow of passengers using HS2 from locations in the South West is probably overstated. This is likely to be greater at a Heathrow station than at Old Oak Common. Heathrow, being further west, reduces the journey time of passengers in Bristol still further and in line with the modelling assumptions would encourage even more trips to and from these areas. Figure 5.3 shows the difference in the destinations of passengers using a Heathrow station compared to Old Oak Common. So a Heathrow station increases the number of HS2 trips to Reading and places close to London (green areas), but it also increases the number of HS2 trips to more distant locations, including Bristol and the South West. These are the areas that are most likely to be over-stated by the model. 53

54 HS2 Demand Model Analysis Figure Change in Number of Passengers on HS2 by Destination when Using a Heathrow Station Compared to Old Oak Common We can also see from this map the negative impact that a Heathrow station has on trips to inner London, which now suffer from an increased journey time as a result of the longer route needed to serve Heathrow. 54

55 Chapter 5: London Interchange Station Location 5.4 Comparison of Heathrow and Old Oak Common Interchange Stations We have so far considered three options for such an interchange station: No Interchange Station Direct, fast trains all the way to Euston Station An interchange station at Old Oak Common with direct connections to GWML and Crossrail. It is assumed all trains on HS2, GWML, Heathrow Express and Crossrail stop at this station A Through Station in the Heathrow area this would mean a revised line of route to run via the Heathrow station (resulting in longer journey times to Euston). The station is a modelling construct with an assumed cross-platform interchange to GWML, Crossrail, Heathrow Express and Heathrow Airport. Again all trains on HS2, GWML, Crossrail and Heathrow Express are assumed to stop at this station. This station would also offer car parking for passengers to drive to the station Table 5.4 shows the numbers of passengers using Euston and the interchange station under each option. Table Distribution of HS2 Passengers using Interchange and Euston Stations London Interchange Passengers going to or from Daily Demand Greater London Airport Access Other Total No Interchange Old Oak Common 31,000 1,000 17,000 50,000 Heathrow through 14,000 2,000 24,000 40,000 Euston Passengers going to or from Daily Demand Greater London Airport Access Other Total Total HS2 Passenger to London No Interchange 113,000 1,000 20, , ,000 Old Oak Common 84, ,000 95, ,000 Heathrow through 79, ,000 88, ,000 55

56 HS2 Demand Model Analysis An interchange station would have a number of benefits and disbenefits: HS2 passengers not using the station would face a longer journey time as the train stops at the station. This would add between 4 minutes at Old Oak Common and 9 minutes 9 at Heathrow. Some HS2 passengers travelling to/from London would gain from reduced journey times. In particular the Crossrail links and frequency at OOC would reduce end to end journey times for several areas in West and East London. Passengers on GWML, Crossrail and Heathrow Express would face longer journeys into Paddington as a result of stopping at Old Oak Common; GWML passengers would face this disbenefit for an interchange at Heathrow too. HS2 passengers from areas to the west and south west of London would see shorter journeys and easier access to reach HS2 services via GWML. The interchange station means these passengers avoid the trip into Paddington and across London to reach Euston. Improved access for passengers travelling to Heathrow for international flights. At Old Oak Common this is in the form of Crossrail and Heathrow Express links to the airport, while a HS2 station at Heathrow is modelled as being on airport. For a Heathrow station there are additional benefits for people who would access the station by car Whether an interchange station is attractive depends on the balance of these various impacts. The balance at an interchange station at Old Oak Common would be overall positive. Despite the significant time penalties of stopping HS2 and GWML trains at the interchange station, the benefits of improved accessibility for HS2 passengers would more than outweigh this. Overall the station increases demand on HS2 by over 7% compared to having no interchange station and delivers net benefits worth around 2bn Comparing a station at Heathrow to Old Oak Common shows a very different pattern of impacts. In the case of Heathrow: There are additional disbenefits for people who use Euston. This is because the route to serve Heathrow is longer and at lower speed (due to tunnel section). A trip to Euston would be up to 5 minutes longer than the equivalent trip via Old Oak Common. Heathrow is also less accessible than Old Oak Common for passengers travelling to and from locations in Central London. The station is served by limited Crossrail services and the Piccadilly line, and is further away from Central London. Old Oak Common on the other hand has very high frequency Crossrail services with much shorter journeys into the centre of London. 9 The main HS2 report states the penalty for stopping trains at Heathrow via a through station is 7minutes whereas in this report we use a 9 minute penalty. This difference is due to late engineering work which has suggested our early estimates of the journey time were overstated by 2 minutes. We have not in the time available re-run the model with this revised journey time, and hence the results presented in this Chapter are on the basis of a 9 minute journey time. We are conducting further analysis on Heathrow which we will publish in due course. However, we do not believe this change in journey time will substantively change our conclusions. 56

57 Chapter 5: London Interchange Station Location However a Heathrow station does improve journey times for passengers travelling to Heathrow, and transferring to/from HS2 to/from locations to the west and south west of London. The station is further to the west, and therefore journey times from a Heathrow station to, say, Reading on the GWML would be significantly faster than the equivalent journey from Old Oak Common These differences are reflected in the modelled number of passengers using HS2, and the places they are travelling to and from. With an interchange at Heathrow, the number of passengers using Euston falls by almost 7% because journey times from Euston to Birmingham and beyond would be longer on a route serving Heathrow. This reduces the attractiveness of HS2 for mode shift (whether from classic rail or car), as well as reducing the number of new trips generated by the scheme The number of passengers travelling to and from locations in Greater London using the Heathrow station is also less than half the number at Old Oak Common since the station is far less accessible for London than Old Oak Common. The average end to end journey time for London passengers is longer using the Heathrow interchange, and this has a significant impact on the attractiveness of the station. This is partially off-set by around 6,000 more passengers using the Heathrow interchange to leave/join HS2 from locations to the west and south west of London, who have shorter journey times on the GWML. However the greater number of passengers going to locations outside London is not enough to offset the loss of passengers travelling to and from London. As a result the overall number of passengers on HS2 with a Heathrow interchange falls by over 10% compared with an HS2 with no interchange. This also has the impact of reducing revenues by some 1.3bn There are some uncertainties in the precise benefits of the station at Heathrow. Our model will understate some of the benefits since it is designed to focus on HS2 passengers. As a result it does not model the demand or benefits of a Heathrow station for people in (say) Reading who might use the station to get to Heathrow via the GWML However there are some areas where the modelling overstates the benefits of a Heathrow station. Firstly, as discussed in Section 5.3, the model may not accurately reflect fares for passengers choosing between direct rail routes and travelling via London. In particular the model assumes all routes have the same fare so Bristol to Manchester costs the same regardless of whether a direct cross-country train is used or travelling via London on HS2. The latter route is likely to cost more in practice In addition the Heathrow station is designed as a modelling construct to identify the maximum demand in each of the markets considered above. It assumes the station is located at Heathrow central terminal area (to maximise connectivity for Heathrow passengers, but also has crossplatform connections to Crossrail and Piccadilly lines), and has a direct (cross-platform) interchange with the GWML. In practice a Heathrow station is unlikely to deliver all of these connections. 57

58 HS2 Demand Model Analysis Overall therefore our conclusion is that a station at Heathrow is less attractive than a station at Old Oak Common. Our modelling suggests that overall there would be significant disbenefits of a Heathrow station compared to Old Oak Common. This is because: A station at Heathrow would cost significantly more than the equivalent station at Old Oak Common. This is equivalent to 2-3bn (PV, 2009 prices). There is a significant reduction in revenues as a result of lower patronage. This would be equivalent to adding 1.3bn to the cost to government of HS2. Overall a station at Heathrow would reduce benefits to HS2 passengers by 2.6bn compared to a station at Old Oak Common. This reflects the fact that the benefits to GWML passengers are not sufficient to offset the additional journey time penalties and longer access times for those travelling to Euston, and more generally to Greater London This suggests that a through station at Heathrow is not attractive for the purposes of HS2. Our model does not, though, have the capability to investigate the benefits of improved connectivity between the airport and passengers in the South East and South West through, for instance, improved connections to the GWML and other rail links such as Airtrack which could be delivered without the need for HS2 to serve a Heathrow station We are continuing to investigate the implications of a station in the Heathrow area to allow a greater understanding of how the impact of issues such as the over-estimation of trips from the South West, and a loop station rather than a through station may have on the business case. We will publish this work in due course, but based on our current understanding of the issues we do not expect this to change the business case substantially We also expect the conclusion to hold for a loop as well as a through station. While a loop would have the advantage of not having any journey time penalty for those on direct trains to London (i.e. not using the loop): Service frequencies would be substantially reduced at the Heathrow station, making it less attractive than Old Oak Common as an interchange for passengers from Reading and other locations outside London. It would not have the accessibility of a station at Old Oak Common for passengers travelling to and from London. 58

59 Chapter 6: Intermediate Station Location

60 HS2 Demand Model Analysis 6.1 Introduction An intermediate station would generate benefits for local passengers by providing fast services into London and Birmingham. In the same way as HS2 can achieve a step change in connectivity for long distance trips, so an intermediate station could provide a step change for shorter distance trips, particularly commuting trips into London This chapter sets out the analysis we used to determine whether an intermediate station would add to the overall business case for HS2. Our approach to intermediate stations consisted of three stages of work: We used analysis from the ready reckoner to consider which locations were most likely to generate significant demand and benefits from an intermediate station. Partial model runs were undertaken to look at the potential benefits to passengers using the intermediate station. Additional analysis considered whether these benefits were sufficient to outweigh the disbenefits to longer distance passengers on HS2. 60

61 Chapter 6: Intermediate Station Locaation 6.2 Determining a Location During the early stages of route design there was a wide range of potential locations for an intermediate station. This included towns within a corridor ranging from Oxford in the south to Luton, Bedford and Kettering in the North. An initial assessment of the level of demand was undertaken for a number of these potential locations as shown in Figure 6.2 below. Figure 6.2 Potential location of Intermediate Stations It became clear that the principal demand would be on commuting trips into London. Whilst there would be some demand for trips into Birmingham, these were much smaller than those to London. For example, the number of passengers during peak hours on the WCML and Chiltern lines into Birmingham is 40% lower than the equivalent flows into London. For this reason, the analysis is restricted to passenger flows between an intermediate station and London. Table 6.2a below gives the annual number of trips between London and the locations considered. 61

62 HS2 Demand Model Analysis Table 6.2a 2004 Annual Rail Demand between London and Potential Intermediate Station Locations Location 2008 Annual Rail Demand to\from London Location 2008 Annual Rail Demand to\from London Aylesbury Vale 0.8m Warwick 0.8m Bicester 0.6m Luton 3.3m Banbury 0.6m Kettering 0.5m Milton Keynes 2.1m Bedford 1.8m Coventry 0.7m Northampton 1.9m Rugby 0.5m Oxford 1.5m Source: PLANET Long Distance From this list, three locations were considered for further work Aylesbury, Bicester and Milton Keynes. These three locations offered the greatest opportunities for demand on a high speed line either with significant demand today, or significant potential for time savings (and therefore demand growth). A station at Oxford was also considered, however the environmental and engineering challenges in serving such a station were significant, and for this reason the station at Bicester was used as an alternative site offering potential connections with Oxford and other Chiltern Line locations These locations were also representative of the various options which remained for consideration after initial sifting of routes. Route options that might have served Luton, Bedford and Kettering were sifted out at an early stage and therefore not pursued for demand modelling purposes. If we had found a compelling case for an intermediate station, we might have reviewed these route options (given the size of the potential market, particularly at Luton). However in practice the conclusions drawn below would apply to any intermediate station. Benefits to Local Passengers The four locations were modelled using PLANET South. We assumed 400m (1,100 seat capacity) high speed trains running from these locations, with time savings of up to 30 minutes over current journey times to London. Table 6.3 gives the results of modelling conducted using PLANET South on the shortlisted station locations. The results suggested that even with significant time savings there would be insufficient demand from Aylesbury to support an intermediate station. However there could be significant demand from a station at either Milton Keynes or Bicester. In both locations, but particularly at Bicester, links with the wider rail network were important in generating demand from the station. 62

63 Chapter 6: Intermediate Station Locaation Table 6.2b - Passenger Volumes and Transport User Benefits from High Speed Rail at Intermediate Station Locations, Excluding Impacts on Other HS2 Passengers Demand in 2033 (passengers in am peak only) Aylesbury Milton Keynes Bicester 1,950 8,700 6,400 Am Peak Hours All Day User Benefits ( m) Revenue ( m) User Benefits ( m) 310 1,680 2,210 Revenue ( m) -70 1, The table shows the benefits from the stations would also be significant, with both Milton Keynes and Bicester offering benefits of m for peak services, rising to bn if services continue throughout the day. The revenues from these stations would more than cover the costs of constructing the station. However this analysis ignores the impact of an intermediate station on other HS2 passengers (and vice versa). Impacts on Wider HS2 passengers Stopping at an intermediate station would have several impacts on long distance HS2 passengers that are the core of HS2 demand: Trains which stop at an intermediate station would add up to 5 minutes onto the journey time to Birmingham and beyond as trains decelerate from top speed, stop at the station and accelerate back to speed. This would reduce the demand and of trips on HS2 over longer distances. HS2 trains would be relatively crowded, particularly in the peaks. This means that in order to meet demand at the intermediate station, there would either be very high levels of crowding, or the train would need to arrive with empty seats. This would limit the number of seats available to long distance passengers and is an inefficient use of capacity. And stopping a train at an intermediate station can have a dramatic effect on the total number of train paths available on HS2 as they decelerate and accelerate away from the station stop We have not explicitly modelled the cost of the time penalty, but it is relatively simple to identify the potential size of this impact. There are two measures that can be used: A station stop would effectively increase journey times between London and locations north of the intermediate station by 5 minutes. Using average values of time, the value of the 5 minute time penalty for stopping a train of 500 passengers would be equivalent to a cost of around 8m (PV 2009). This is equivalent to 800m if three trains per hour in each direction stop throughout the day 63

64 HS2 Demand Model Analysis Data from early model runs suggests the impact of a 1 minute longer journey would be to reduce the benefits of HS2 by around m. This suggests stopping every train would have a disbenefit of 1.5-3bn. Stopping three trains per hour is equivalent to around 25% of trains, which suggests a disbenefit of around bn Using either method it is clear that the cost to through passengers is likely to be significant, but this penalty alone does not outweigh the benefits to local passengers at the intermediate station. This suggests that if we could provide sufficient capacity to an intermediate station without impacting on the capacity of the main line then an intermediate station could be attractive However in practice the impacts of an intermediate station on capacity are likely to make such a station unattractive. Two points are of particular importance: Trains using HS2 are forecast to be relatively full with long distance passengers (particularly during peak hours). Hence the additional demand from an intermediate station would either create significant additional crowding, or require additional services to be run for which there is insufficient capacity. Trains stopping at the intermediate station would result in the loss of up to 1 train path per train stopping. So stopping three trains per hour would effectively consume 20% of the capacity of HS These impacts on capacity have significant implications for the design of a wider high speed network. In particular it would effectively preclude the extension of HS2 to serve Leeds and other new markets to the east of the country. As discussed in chapter 11, the potential benefits for such an extension are likely to significantly outweigh the benefits of an intermediate station As a result we concluded that an intermediate station would have a detrimental impact on the case for high speed rail, particularly in the long run. 64

65 Chapter 7: Central Birmingham Station Location

66 HS2 Demand Model Analysis 7.1 Introduction This chapter summarises the demand and appraisal analysis underlying our recommendation on the location of a station in Birmingham city centre. The preferred station site is at Fazeley Street, adjacent to the existing Moor Street station and immediately to the north of the WCML leading into New Street station All of the station locations considered by HS2 were close to central Birmingham in a similar location with similar access characteristics. Birmingham New Street would offer benefits in terms of improved interchange opportunities, but the engineering challenge, and the impact on capacity on the classic rail network meant this option was not taken forward. Our demand modelling was not sensitive enough to pick up differences in demand that might result from other station locations, and therefore wider engineering and environmental considerations drove the choice of station. Analysis of demand was instead used to determine the overall market for a central Birmingham HS2 station, as well as the impact of HS2 on existing rail services serving Birmingham. 7.2 The Impact of HS In the absence of HS2, rail demand at Birmingham New Street and Moor Street is set to grow between now and 2033 by around 65%, increasing from 141,000 to 232,000 users per day. This represents boarders, alighters and interchange passengers, but not through passengers on all short and long distance services Table 7.2 outlines the impact of HS2 at the major Birmingham Stations both classic and high speed rail. Building HS2 into Birmingham Fazeley Street would see Fazeley Street used by 31,000 HS2 passengers per day in 2033 in our central case. Around 25-30% 10 of these passengers would use classic rail services into New Street or Moor Street in order to access HS2 services. The rest would access Fazeley Street by walking, using non rail public transport or car. Our models are not detailed enough to understand the impact of HS2 on the local road or bus networks, although we do not consider that this issue will have a significant impact on the choice of central Birmingham station location. 10 The National Rail Travel Survey suggests that 30% of New Street Passengers use local rail services to access or egress the station. PLANET is forecasting 25%. 66

67 Chapter 7: Central Birmingham Station Location We forecast that New Street would see a net reduction of 36,000 passengers per day which would help overcrowding at New Street as well as the surrounding local transport network. Moor Street would see a net increase of 3,000 passengers per day. The change in demand at New Street and Moor Street is driven by the following behaviours: Reduced demand as a result of passengers transferring from classic rail long distance services onto HS2 services using Fazeley Street or Birmingham Interchange. Increased demand as a result of new HS2 passengers using local rail services in order to access Fazeley Street. Increased demand as a result of new classic rail passengers on services on the classic rail network using capacity released by HS2. Table 7.2 All day Demand at Birmingham Stations with and without HS2 Daily Boardings and Alightings (including interchanges) 2033 Without HS With HS2 with Parkway 2033 With HS2 without Parkway Moor Street 19,000 22,000 24,000 New Street 213, , ,000 International 28,000 14,000 16,000 HS2 Fazeley Street 0 31,000 50,000 HS2 Parkway 0 23,000 0 TOTAL 259, , ,000 Note: This data is a combination of long distance all day demand extracted from PLANET Long Distance and PLANET Midlands short distance demand from the 7-10am morning peak. We have applied a factor of 3 to convert the peak demand to all day demand and produce total all day demand The impact of an HS2 Birmingham Interchange station near Birmingham International reduces the number of passengers using Fazeley Street. Without the interchange station an extra 19,000 people per day would use Fazeley Street. As described in chapter 2, the station choice model determines the demand for each station based only on car accessibility. This means that Fazeley Street, which is more accessible by public transport than the interchange station, may get more passengers than our modelling suggests. Summary An HS2 station at Fazeley Street would be used by 31,000 passengers per day (boarders and alighters), with 25-30% accessing this station by rail. New Street would see a net reduction of 36,000 passengers per day while Moor Street would see a net increase of 3,000 passengers per day. 67

68 Chapter 8: Birmingham Interchange Station Location

69 Chapter 8: Birmingham Interchange Station Location 8.1 Introduction This chapter summarises the analysis underlying the recommendation of the HS2 report to include an interchange station near Birmingham International Airport. Its structure mainly follows the work as it evolved over time. Section 8.2 summarises the early analytical approach that identified potential locations for an interchange station on the outskirts of Birmingham and also covers the selection of a shortlist of options. Section 8.3 outlines the selection of a location near Birmingham International Airport and section 8.4 the business case. 8.2 Option Sifting Initially we examined a number of potential interchange stations around the outskirts of Birmingham from the north-west (Walsall/ Wolverhampton) to the south as far as Warwick Parkway. These locations were selected to investigate different types of potential markets, rather than reflecting preferred locations or route choices. The aim of this analysis was to understand whether different parkway locations, particularly to the North or West of Birmingham, would have a significant enough impact on demand to overcome separately identified engineering and environmental issues Table 8.2 shows the number of people living within a 45 minute car journey time of different areas of Birmingham, as well as the number of car trips made between London and that catchment area. The former measure gives an indication of the potential for demand on HS2, the latter represents one measure of existing demand and the potential for mode shift. The largest populations are generally found around locations to the north and west of Birmingham including sites close to Wolverhampton, Walsall, Dudley and Castle Bromwich. Although areas to the south east of Birmingham have somewhat lower population densities, there are many more car trips to and from London, in part because accessing London is much easier. 69

70 HS2 Demand Model Analysis Table 8.2: Population and Car Journeys to London within 45 minutes of potential interchange station locations Area 2001 Population Car Trips to or from London Daily Solihull 817, Birmingham International 1,058, Warwick 612, Birmingham SE 927, Birmingham South 1,252, Coventry North 660, M42 North east 960, Castle Bromwich 1,303, Wolverhampton 1,292, Walsall 1,253, M54 North 1,000, Dudley 1,214, Source: West Midlands PRISM Model Analysis of existing rail journeys from the West Midlands to London and the South East reveals a similar pattern: generally the zones to the south east of Birmingham have the strongest existing demand. This picture is even stronger if we only consider those travellers who access the station by car. Our analysis at this stage was therefore suggesting two distinct areas of demand: To the north and west of Birmingham, there was a large potential market and also the scope that these areas would gain significant time savings on a rail journey to London (in some cases up to 1 hour). To the south and east there was a good existing market and scope for mode shift but perhaps slightly lower benefits per trip Engineering work on the Birmingham central station and line of route, suggested that any route options through Birmingham and on to the potential parkway locations to the North West would at best be extremely expensive (see HS2 s report). Whilst the area to the North West of Birmingham has higher population and potential demand, simple elasticity 11 based demand analysis did not suggest sufficient evidence to suggest benefits would be enough to overcome the cost and technical challenges of reaching a station in these locations. Therefore interchange stations to the north west of Birmingham were not taken forward for more detailed consideration. 11 The application of elasticities has limitations in cases when there are large changes in journey times as would potentially be the case here. However, demand would need to be very high (compared to the south and east) to overcome the substantial difficulties with a line of route to serve the interchange locations to the north and west of Birmingham. 70

71 Chapter 8: Birmingham Interchange Station Location On the basis of the demand analysis, and following stakeholder consultations, three locations were identified for more detailed analysis Solihull, near Birmingham International Airport, and Water Orton. All of these lie to the East and South East, coinciding with the M42/M6 corridor and providing good connections to the road network. These connections were particularly important to improving both the accessibility of the station and the potential for mode shift. 8.3 An Interchange near Birmingham International To test the relative merits of the three shortlisted stations in terms of demand, we used a near final version of the model to test each option. Subsequent to this work, the model underwent further improvements in the way the London station location is represented. However, in terms of calculating the relative demand or benefits between the three Birmingham interchange options, there should be little difference between the interim version used and the final model For comparative purposes, we used an indicative train service specification that assumed only services between Birmingham and London stop at the interchange station, with all other HS2 trains passing through non-stop. This is not to say there is no case for stopping other trains at the interchange, rather that in the time available for testing between different station locations we did not include these markets. We also did not allow passengers to travel between the interchange station and central Birmingham The demand and benefits of all three locations are remarkably similar. On the measure of overall benefits, the highest is less than 2% above the lowest. Even on the individual measures of leisure or business time savings and revenue the largest differences do not exceed 10%. Against the uncertainties generally involved in modelling, these differences are not significant. The three stations would be seen as near perfect substitutes from a demand and benefits aspect This insight allowed us to focus on engineering and environmental considerations in order to identify the optimal location for a potential Interchange station. As outlined in HS2 s report, the work on preferred line of route led to the exclusion of the Solihull corridor. A station at Water Orton would be consistent with the line of route. However, constructing a station close to the proposed delta junction would most likely incur much larger costs than choosing Birmingham International Airport instead Birmingham International Airport was therefore selected as the best candidate. It also provided the best fit with development aspirations in the area and was strongly supported by stakeholders. These aspirations may also enhance the economic case that we have modelled for an HS2 interchange station in this area. 71

72 HS2 Demand Model Analysis 8.4 Demand and Benefits of Birmingham Interchange Having identified the best location for a Birmingham Interchange at a location near Birmingham International Airport, we tested its overall contribution to the business case and whether an interchange station should be part of the preferred scheme. The interchange station benefits passengers who have easier access to an interchange than a central Birmingham station. Some interchange passengers would not choose to travel on HS2 in the absence of a station, while some passengers would instead use central Birmingham but suffer a slower journey. In addition, the journey time to London is assumed to be nine minutes shorter from the Interchange than from the central station On the other hand stopping trains at an interchange creates a longer journey time for through passengers not using the station. We have estimated trains from London to central Birmingham will take five minutes longer if they stop at Birmingham Interchange on the way, as the trains would not be travelling at top speed at this point The modelling suggests that the balance between these two opposing effects is positive. The overall benefit to users is likely to be just less than 1bn, in present value terms. It not only benefits passengers using HS2 but increases demand for HS2 services and so delivers additional revenue worth 300m to off set the costs of building the station We estimate that 40-50% of people travelling to or from Birmingham would be using the interchange station. Figure 8.4a below shows the origin/destination for which travellers prefer it over the central station in blue. 72

73 Chapter 8: Birmingham Interchange Station Location Figure 8.4a Proportion of Passengers Choosing to use Fazeley Street and Birmingham Interchange by Area This shows that some travellers choose the interchange station even though they are starting from/ travelling to a location fairly close to the central station as their total journey time is optimised. Figures 8.4b and 8.4c show the minimum access time to a high speed station without and with an interchange station at Birmingham International. These show the significant improvements to accessibility for residents in the districts to the East of central Birmingham. The interchange station is accessible in close to 30 minutes for residents in a wider corridor from Rugby and Coventry in the south east to Hednesford and Burton upon Trent in the north. 73

74 HS2 Demand Model Analysis Figure 8.4b Minimum Access Time to Fazeley Street by Origin Zone 74

75 Chapter 8: Birmingham Interchange Station Location Figure 8.4c Minimum Access Time to Fazeley Street or Parkway by Origin Zone As outlined above, the area around Birmingham International Airport exhibits strong highway demand to London. The model suggests a slight decrease in the flow of car journeys between the two areas due to introducing the interchange station. This difference in road trips implies for example around 300 fewer car journeys on the M1 on an average day Our proposals for the interchange station include car parking and new connections onto the strategic road network (see HS2 main Report and Arup supporting documentation). Our estimate is that in 2033, the interchange station would attract a net addition of cars trips to the area during the morning peak hour. The highway impacts of this have been modelled using the West Midlands multi-modal transport model PRISM. The results do not appear to indicate a significant worsening in performance in addition to that caused by background growth. 75

76 HS2 Demand Model Analysis Appraisal of Birmingham Interchange HS2 s report sets out an estimated construction cost of 465m for the interchange station. For the appraisal, this figure was adjusted to 535m to include optimism bias, market prices and discounted to a 2009 present value. In addition, station operating and maintenance costs were estimated at around 76m (PV, 2009) to make a total present value of costs of 611m. Finally, the increased spending on rail fares and reduction in car fuel consumed would lead to a loss in indirect tax of around 17m Net of changes in revenue, the present value of costs comes to around 340m ( 611m construction and operating costs offset by 271m revenue). With benefits of just under 1bn, the benefit cost ratio is 2.9 (excluding WEBS). This delivers a robust business case for including an interchange station in the preferred scheme. 76

77 Chapter 9: Connections to High Speed One

78 HS2 Demand Model Analysis 9.1 Introduction We were asked to review options for linking HS2 with HS1. This chapter sets out the methodology and assumptions used to analyse the different options under consideration. The analytical approach that has been developed for this purpose is far simpler than the approach used for analysing other elements of HS2 as set out elsewhere in this report. In this case the approach is designed to provide an indicative estimate of the potential demand for international travel via different types of HS1 connections and services, and the likely business case of each option. 9.2 Our Approach to Modelling International Demand Our approach to forecasting the potential rail demand for international trips has been developed by the consultancy SKM and implemented within a spreadsheet model. The approach uses data collected from a number of different domestic and international rail corridors to understand the rail market share for different journey times (particularly drawing on work by Steer Davies Gleave 12 ). Figure 9.2 shows each of these data points as dots, from which a single functional relationship (logit curve) was derived between journey time and mode share and as shown by the curve. 12 Steer Davies Gleave (2006) Air and Rail Competition and Complimentarity. Prepared for European Commission DG TREN 78

79 Chapter 9: Connections to High Speed One Figure 9.2 Relationship between Rail Journey Time and Market Share 100% 90% 80% Rail share of Total Market pre Rail market share 70% 60% 50% 40% not high speed logit curve 30% 20% 10% 0% Rail Journey Time (mins) The data points and corresponding logit curve in Figure 9.2 are based only on the rail journey time, and hence take no account of elements of generalised cost such as frequency, crowding, fare or check in time. The calibration of the logit curve is based on existing markets in which rail and air successfully compete. We assume therefore that relative fares between rail and air do not change with the introduction of HS2 and are similar to other markets where rail and air compete. We also do not take account of differences in service frequency that might occur in the scenarios considered below, although we note the implications in our conclusions There is rather more ambiguity as to whether implicit within the logit curve is the inclusion of a check in time for international services. Many of the data points in Figure 9.2 are based on domestic markets where check in time does not exist. This does not relate to whether a passenger has to check in for international services at some point on their journey - in all scenarios we assume they do rather whether this time should be included or excluded in the calculations used in the logit model for forecasting rail mode share. 79

80 HS2 Demand Model Analysis To reflect this uncertainty we have undertaken a range of sensitivity tests in which we vary the check in time of both the reference case (without HS2) and the HS2 scenario under test. The numbers we report here use a mid point based on a check in time of 30mins, with the low end of a range based on a check in time of 65minutes and the high end based on 0 minutes. This variation in check in time can make a significant difference to the demand, roughly doubling the number of international rail trips The model for estimating the demand for international rail travel then makes use of the logit relationship derived in Figure 9.2 by applying the following approach: The current end to end rail journey times between several major UK and continental cities were calculated and are shown in Table 9.2a below. These cities were chosen as they were felt to represent the biggest potential markets for international rail travel that might use HS2. The overall journey times were calculated from existing timetables and included the time spent on board a train, as well as a 40 minute penalty for making an interchange in London and a 15 minute penalty for making an interchange on the continent. As already described we also included a 30minute check in time penalty within a range of 0-65minutes. Using these journey times, rail s likely overall share of the market was estimated using the logit function shown in Figure 9.2. For instance, if the overall rail journey time between two places is 200 minutes then we would expect rail trips to constitute half of the total rail/air market. Forecast data on the expected size of the future air market between each of the modelled city pairs was provided by DfT and taken from their air passenger forecasting model. Applying rail s market share to the total air market establishes the size of the rail market. This is converted to a daily total using an annualisation factor of 300. In the absence of HS2 (our reference case) the expected number of daily rail trips between various city pairs is shown in Table 9.2b. It can be seen that the total number of international rail trips between the continent and Birmingham, Manchester, Liverpool and Glasgow is approximately 1,700 trips per day (in both directions). The biggest markets by a considerable margin are Birmingham and Manchester to Brussels and Paris, with Paris being double the market than Brussels and Birmingham a slightly larger market than Manchester. The impact of different high speed rail connections can then be modelled by adjusting the rail journey times to reflect different types of international connection or service and seeing how the size of the rail market will change. It is worth noting that in this approach improved rail journey times will capture a bigger proportion of the air market, but the approach will not grow the overall size of the market. 80

81 Chapter 9: Connections to High Speed One Table 9.2a -Current End to End Rail Journey Times without HS2 (Reference Case) Rail Journey Time (mins) Amsterdam Brussels Paris Cologne Frankfurt Lyon Birmingham Manchester Liverpool Edinburgh Glasgow Table 9.2b Daily 2-way International Rail Trips without HS2 (Reference Case) Daily Demand Amsterdam Brussels Paris Cologne Frankfurt Lyon TOTAL (Range) Birmingham Manchester Liverpool Edinburgh Glasgow ( ) 680 ( ) 190 ( ) 40 (20-50) 0 (0-10) TOTAL (Range) 50 (30-80) 560 ( ) 1,100 ( ) 0 (0-0) 10 (10-20) 0 (0-0) 1,730 ( ) 81

82 HS2 Demand Model Analysis 9.3 Analysis of Different International Connections and Services We reviewed four scenarios for connecting HS2 with HS1: Running direct international high speed services between Birmingham, Paris and Brussels via a connection between HS1 and HS2. Potentially these direct services could also run to other destinations North of Birmingham. Running direct international high speed services between Old Oak Common and Paris and Brussels via a connection between HS1 and HS2. This would allow all HS2 passengers (not just those from Birmingham) an easy interchange onto HS1 services at Old Oak Common, and potentially a higher frequency international service. Not doing anything to improve connectivity between HS2 and HS1, and simply allowing passengers to transfer between Euston and St. Pancras by existing means (walk, tube, bus, or taxi). A people mover between Euston and St Pancras to make the transfer between these stations quicker and easier than at present. This might also benefit domestic passengers if it aided dispersal at the station The key variables for modelling each of these scenarios are our assumptions on the time taken to interchange between HS2 and HS1, the frequency of train services and variation in journey time. For all the scenarios it is assumed that there is a 30 minute reduction in journey time between London and the North as a result of HS2 trains travelling faster than the existing classic line. In addition, each scenario makes different assumptions about the size of the London interchange penalty. Table 9.3a below summarises how the existing rail journey times in Table 9.2a would change in each of these scenarios. We have not tried to accurately reflect the different advantages or disadvantages of different frequency levels expected under each scenario or the small variations in journey time provided by different route alignments for the connection between HS2 and HS1. Table 9.3a J ourney Time Savings for Different Types of HS2-HS1 Services Compared to the Reference Case without HS2 Scenario Saving on existing rail journey Time (mins) Saving on existing interchange penalty (mins) Total saving on existing rail journey time (mins) Direct international services HS1 Interchange at Old Oak Common Walk between Euston and St Pancras Euston to St Pancras People Mover

83 Chapter 9: Connections to High Speed One For the first scenario, in which fast non-stop dedicated services run straight between Birmingham and Paris and Brussels, our modelling estimates that by 2033 this would attract around 900 passengers to and from Paris and 700 passengers to and from Brussels per day, as shown in Table 9.3b. Even if the existence of a high speed service generated significant additional international travel, demand is unlikely to be enough to offer a reasonably frequent service which will further penalise the attractiveness of this option If hybrid direct international services ran on HS2 and then on classic lines to other destinations such as Manchester, Liverpool and Scotland this might generate a further 1,500 passengers to Paris and 500 passengers to Brussels in each direction per day. Table 9.3b Daily 2-way International Rail trips with Direct HS2-HS1 Services Daily Demand Amsterdam Brussels Paris Cologne Frankfurt Lyon TOTAL (Range) Birmingham Manchester , Liverpool Edinburgh Glasgow ,640 ( ) 1,560 ( ) 430 ( ) 80 (50-120) 10 (10-20) TOTAL (Range) 140 (90-220) 1,140 ( ) 2,400 ( ) 10 (10-10) 30 (20-50) 10 (0-10) 3,720 ( ) For the second scenario, in which some HS1 trains run direct between Old Oak Common rather than St. Pancras and Paris and Brussels, our modelling suggests that by 2033 this would attract 2,200 passengers to and from Paris and 1100 passengers to and from Brussels per day as shown in Table 9.3c. Although the demand from Birmingham would be less than in the first scenario, more UK destinations would have access to Old Oak Common using HS1 domestic trains and hence overall demand for international services would be higher. It is also likely that Old Oak Common would offer a higher international train frequency than would be possible running direct international trains from Birmingham This analysis does not include demand from non-hs2 users, particularly from West London and the Thames Valley, who might find Old Oak Common easier to access than St Pancras. Such services could be expected to attract some of the market that would otherwise have flown from Heathrow, as well as some who would otherwise have travelled from St. Pancras. 83

84 HS2 Demand Model Analysis Table 9.3c Daily 2-way International Rail trips with a Change at Old Oak Common Daily Demand Amsterdam Brussels Paris Cologne Frankfurt Lyon TOTAL (Range) Birmingham Manchester Liverpool Edinburgh Glasgow ,520 ( ) 1,400 ( ) 390 ( ) 70 (40-110) 10 (10-20) TOTAL (Range) 120 (70-190) 1,050 ( ) 2,180 ( ) 10 (0-10) 30 (20-40) 0 (0-10) 3,400 ( ) For the third scenario, in which people to walk, or use existing public transport to interchange between Euston and St Pancras, our modelling suggests in 2033 this would attract 1,600 passengers using HS2 to or from Paris and 800 to or from Brussels as shown in Table 9.3d. Although walking between Euston and St Pancras would attract a high journey time penalty, especially with luggage, St Pancras is likely to offer more frequent HS1 services to the continent than would be available from Old Oak Common. Table 9.3d Daily 2-way International Rail Trips with a Walk between St. Pancras and Euston Daily Demand Amsterdam Brussels Paris Cologne Frankfurt Lyon TOTAL (Range) Birmingham Manchester Liverpool Edinburgh Glasgow ,160 ( ) 1,010 ( ) 280 ( ) 50 (30-70) 10 (0-10) TOTAL (Range) 80 (50-120) 790 ( ) 1,600 ( ) 0 (0-10) 20 (10-30) 0 (0-0) 2,500 ( ) 84

85 Chapter 9: Connections to High Speed One The final scenario, in which a light-rail link or people mover from Euston to St Pancras is provided, would increase the demand closer to the levels of an interchange at Old Oak Common as shown in table 9.3e. Table 9.3e Daily 2-way International Rail Trips with a People Mover between St. Pancras and Euston Daily Demand Amsterdam Brussels Paris Cologne Frankfurt Lyon TOTAL (Range) Birmingham Manchester Liverpool Edinburgh Glasgow ,390 ( ) 1,260 ( ) 350 ( ) 60 (40-90) 10 (10-10) TOTAL (Range) 110 (60-170) 960 ( ) 1,980 ( ) 10 (0-10) 20 (10-30) 0 (0-10) 3,100 ( ) 9.4 Appraisal of Journey Time Benefits Along with our modelling of demand, the appraisal of benefits also follows a simple approach. We have estimated the benefits of each scenario by comparing the change in journey times and demand with our reference case in which HS2 is not built. Standard appraisal approaches were applied to value this time saving and estimate the average benefit per passenger, 13 which were then discounted over 60 years to give a present value. The results of this are summarised in Table 9.4, with the range reflecting different assumptions about check in times as described in T he benefits have been calculated using the rule of half to estimate the welfare benefits from the time saving that would be generated by these trips. This implicitly assumes that there is a linear relationship between the cost of travel and demand, and that for some passengers the value of the trip may not equal the full time saving. The approach is described in more detail in DfT s WebTag guidance : 85

86 HS2 Demand Model Analysis Table 9.4 Summary of Benefits for Different Types of HS2 HS1 Services Scenario Direct international services to Birmingham Direct international services to Birmingham, Manchester, Liverpool and Scotland HS1 Interchange at Old Oak Common Walk between Euston and St Pancras Euston to St Pancras People Mover Total Daily Demand (two way flow between all destinations with range) 1,600 ( ) 3,700 ( ) 3,400 ( ) 2,500 ( ) 3,100 ( ) 60 Year Appraisal of Benefits 2009 prices (with range) 300m ( ) 650m ( ) 500m ( ) 220m ( ) 410m ( ) Depending on the choice of alignment, the capital costs of a direct link vary from 1-3.5bn. It is unlikely that any option will cover the capital costs, and once operating costs are included the benefit cost ratio is likely to be significantly below 1. The strongest case is likely to be a connection with a people mover at Euston, which could add around m of benefits at much lower cost As described, these results are based on fairly simplistic analysis. The analysis does not include the impact of: How overall market for international travel might change as a result of new rail services. This means there is no generated demand, which might cause the demand and benefits to be somewhat underestimated. The considerable differences in frequency of international services likely to operate under each scenario. It is unlikely for instance that the frequency of direct international services from Manchester or Birmingham will ever be as high as from London. This could overestimate the demand and benefits for the scenarios running direct international services. The potential for non-hs2 passengers to use international trains from Old Oak Common or use a people mover between Euston and St. Pancras. This could underestimate the demand and benefits of these scenarios. How international air and rail fares might change compared to existing levels, or how airlines might respond to this increased competition Nevertheless this analysis does provide a good indication of the likely levels of demand for international rail travel north of London. Whilst more refined analysis may change the forecast number of HS2 passengers making international trips, there would need to be significantly higher demand to deliver a positive business case. Given the overall market this would seem unlikely and we therefore consider our approach robust to support the broad conclusions that have been drawn. 86

87 Chapter 9: Connections to High Speed One 9.5 International Connections as Part of a Wider Network The business case for running international services on HS2 would be improved if HS2 was part of a wider high speed network to other parts of the UK. Assuming a best case scenario in which high speed international trains serve all of the UK cities directly, the total international demand would be 4,300 passengers per day as shown in Table 9.5 below. This would generate benefits in the region of 550-1,200m. Table Daily 2-way International Rail Trips with Direct International Services on a Wider HS2 Network Origin/ Destination Amsterdam Brussels Paris Cologne Frankfurt Lyon TOTAL (Range) Birmingham Manchester , Liverpool Edinburgh Glasgow ,640 ( ) 1,870 ( ) 520 ( ) 250 ( ) 40 (20-60) TOTAL (Range) 180 ( ) 1,260 ( ) 2,830 ( ) 10 (10-20) 40 (20-50) 10 (0-10) 4,300 ( ) Summary Based on current travel patterns and behaviours, the passenger market wishing to use a link between HS1 and HS2 would be relatively small. Even under a wider network with direct international services the benefits are unlikely to outweigh the costs. We recognise the uncertainty in aviation policy in the long term and the difficulty in forecasting the airlines reaction to a rail link, both of which could change the future size of the market. However there would need to be a significant increase in demand to change the conclusions outlined here. 87

88 Chapter 10: The Overall Business Case for HS2

89 Chapter 10: The Overall Business Case for HS Introduction We have in previous chapters set out the analysis that supports the decisions taken by HS2 and the overall design of the scheme. This chapter draws together these elements to consider the strength of the business case for the preferred scheme. It begins by setting out our forecasts of demand for HS2, before moving on to consider the costs and benefits of the scheme. It concludes by looking at the overall value for money, attempting to weigh the substantial financial and economic impacts against the environmental and social impacts that will also occur Passenger Demand for HS We set out in Chapter 1 our view of the world in 2033 without HS2. This shows substantial growth in demand for long distance rail trips and substantial increase in crowding on the WCML. Between 2008 and 2033 we forecast that demand on the WCML will double, mainly driven by people s propensity to travel further and more frequently as they grow wealthier. Table 10.2a sets out the forecast change in demand without HS2 between London and the key cities that would be served by HS2. Table 10.2a - Number of Daily Passengers to and from London without HS2 To/from London Birmingham 8,300 20,500 Manchester 7,300 20,300 Liverpool 2,900 8,200 Glasgow 1,400 6, With HS2, journeys between London and Birmingham, Manchester, Liverpool and Glasgow would be up to 30 minutes faster than current services. A new high speed line would also allow a more frequent and reliable service, with greater rail capacity provided to Birmingham (particularly in the peak) These improvements in travel time and experience would attract significant numbers of passengers onto the high speed trains. Around 145,000 would use HS2 itself providing faster journeys to London. A further 15,000-20,000 passengers would use classic compatible trains without travelling on the high speed line itself. These journeys are between places such as the north of England and Scotland where HS2 classic compatible services replace the existing classic rail service Figures 10.2a and 10.2b below, show the change in long distance passenger flows when HS2 is operational and the percentage loading factors on the long distance trains along the WCML and HS2. North of Birmingham the demand for WCML and HS2 are combined as both will use the same tracks. Here we see significant increases in passenger flows along the WCML. There would also be a significant net increase in long distance flows using the WCML and HS2 south of Birmingham. Overall the number of passengers on this corridor would increase by around 61,000 (a 57% increase). This is made up of a reduction of some 84,000 trips on the WCML into London and an increase of 145,000 trips on HS2. The HS2 services would be well used with average load factors above 60%. 89

90 HS2 Demand Model Analysis Figure 10.2a Change in Long Distance Daily Rail Trips Resulting from HS2 in 2033 Glasgow s n r Change in long distance daily trips after the introduction of HS2, in ,850 e a t e 16,810 or Leeds e Hull H l 22,302 3 Liverpool v r o o l Manchester M n c r Sheffield S e fii el d 28,395-19, ,473 Stoke-on-Trent e-on-trn nt t Nottingham ti m -45,227 7 Leicester c e t r Peterborough r o r ou h i rm in n h m Change in volume (Day 1c vs. DM) Legend More than 20,000 20,000 to 10,000 10,000 to 3,000 3,000 to -3,000-3,000 to -10,000-10,000 to -20,000 Less than -20,000 Bristol r t l 145,391 3 Oxford d Reading e d n -84,326 London 90

91 Chapter 10: The Overall Business Case for HS2 Figure 10.2b 2033 Rail Load Factors with HS2 Glasgow w 43 din r g h 60 Forecast daily load factors on long distance services after the introduction of HS2, in e a t e 52 York Leeds e Hull 69 Manchester n e t err Liverpool r o o l Sheffield f field d e on en t Nottingham t Leicester i s r et r oro u h ir m in gha am Day 1c Crowding Legend (Volume over seats) More than 80% 60% to 80% 40% to 60% 20% to 40% 0 to 20% Cardiff C r f r s OxfordO fo r d Reading London 91

92 HS2 Demand Model Analysis These flows represent a substantial increase in passengers, particularly over longer distances. For example the number of rail passengers travelling between Scotland and London increases by almost 60% (with over 11,000 passengers using HS2 and a reduction of around 4,000 Classic rail passengers). And flows on the WCML south of Glasgow more than double. Such substantial increases could be driven by two impacts: Faster journeys and more access to other locations will attract more people to travel, and travel more often (trip generation); Reductions in journey times may make rail more competitive with other modes (particularly air travel in the case of Scotland), driving modal shift Table 10.2b shows the increase in the number of rail trips (both HS2 and Classic rail) to London. There is an increase of around 7,200 trips between Scotland and London (both directions). The majority of these trips (59%) would otherwise have used air to travel. Only around 2,800 of these trips are new trips that are generated by the journey time savings from HS2. Table 10.2b Increase and Source of Rail Trips (Both High Speed and Classic rail) to and from London as a Result of HS2 Daily Demand To/From London Increase in Rail Passengers (HS and Classic) Source of Additional Rail Passengers Car Air Generation Scotland 7,200 1% 59% 40% North West 15,900 6% 17% 76% West Midlands 12,200 24% 0% 76% At first glance it appears surprising that there would be such a large mode shift from Glasgow, given that HS2 trains would still take 4 hours to reach Glasgow and gain only a relatively small improvement in journey times of 30 minutes. However international and historical experience of HSR suggests that journey times of around 4 hours are where the rail market share is most sensitive to changes in rail journey times. Chapter 9 describes some of this evidence, which also underpins our model of international rail demand. This data suggests that for journey times within the range of 1 ½ hours to 5 hours, a ten minute time saving would increase the market rail market share by 3-4% Applying this data to the market between Glasgow and London suggests a reduction in rail journey time from 4 ½ hours to around 4 hours would imply rail market share would rise from around 28% without HS2 to about 38% - an increase of over one third. In practice the rail market share for Scotland without HS2 is forecast to be 34%, slightly higher than the historical and international average for journey s over this distance. Our modelling forecasts this will increase to around 50% - an increase which is broadly in line with the increases that have been seen in past schemes. 92

93 Chapter 10: The Overall Business Case for HS Trip generation becomes more important for journeys over shorter distances, where air is a less important mode. These new trips account for over 75% of the increase in demand for rail travel between London and the West Midlands and North West resulting from the introduction of HS2. However, whilst trip generation is a more significant part of the increase in rail demand, Table 10.2c shows that this represents just 20-30% of passengers on HS2. Over these distances, shift from existing classic rail services becomes a more significant factor in HS2 demand. On average around two thirds of passengers between London and the West Midlands and North West would otherwise have travelled by classic rail. Table 10.2c: HS2 Daily Demand to/from London Daily Demand Total HSR West Midlands 40,100 North West 54,700 Scotland 11,300 Rest of the Country 9,100 Total 115,200 Source of HS2 Passengers Classic Rail Road Air Generated 28,000 70% 38,800 71% 4,100 36% 5,500 61% 76,400 66% 3,000 7% 1,000 2% 100 1% 5,000 55% 9,000 8% 0 0% 2,700 5% 4,200 38% 0 0% 7,000 6% 9,200 23% 12,200 22% 2,800 25% 2,600 29% 26,800 23% People would travel on HS2 for a range of reasons. Faster journeys would attract more business travel. Our modelling suggests one third of HS2 passengers would be undertaking business trips, with a 10% overall increase in the number of long distance business trips as a result of HS2. The majority of passengers (70%) would be people travelling for other purposes, with leisure trips likely to be particularly important HS2 Appraisal Costs For appraisal purposes, we consider all types of costs and need to be able to represent them in a single figure, the Present Value of Costs (PVC). For this purpose we discount all future expenditure back to and keep all prices constant at 2009 level. The same approach is taken for benefits as well as revenues. The document HS2 Cost and Risk Model provides the full detail on how the various costs and rates have been derived. Here we focus on how these have been converted into an appraisal PVC. 14 The green book discount rate is 3.5% for the first 30 years, falling to 3% for the next 30. In agreement with DfT we assume the 30 year period begins with scheme opening (in 2026). Thus the 3.5% rate is used for all costs/benefits accruing before 2056, 3% thereafter. 93

94 HS2 Demand Model Analysis HS2 Capital Costs Paragraph of the HS2 Cost and Risk Model shows the central estimate of construction costs for HS2 to be 12.3 billion (2009 prices) including quantitative risk assessment. Section 7 of the same document explains the reasoning behind applying a further optimism bias of 34.3% to this which brings the total cost of construction to 16.5bn Figure 1 of Ernst & Young s report Financial considerations a report for HS2 shows how this total cost is split over the years preceding the opening of HS2 (assumed to be December 2025). Discounting this profile of costs, the 2009 present value of all construction costs is 11.4 billion In line with WebTAG guidance 15 we have converted this figure into the market price unit of account. This represents an adjustment for taxation and government funding to ensure that costs are on a comparable basis to the benefits estimated by the demand model. The final PV for appraisal purposes is 13.7 billion In addition to the initial costs of construction, some elements of HS2 infrastructure would need substantial renewal and reconstruction during the 60 year period over which we appraise HS2. The overall impact of the following assumptions is to increase the capital costs of the scheme by 1.1bn (PV, 2009 prices). Civils and structures Asset life greater than 60 years, and therefore no renewal costs during the appraisal period Railway systems 100% renewal after 30 years Control systems 100% renewal after 15 years Stations complete renewal of some elements of construction after 40 years Depots 50% renewal after 30 years Paragraph of the HS2 Cost and Risk Model provides the cost of rolling stock including risk and optimism bias as 2.84billion. The rolling stock is expected to have a useful life of 35 years. To appraise the full costs over the 60 year appraisal period, we have assumed that the full stock will be replaced after 35 years at the same cost in real terms As a 2009 present value converted into market prices rolling stock capital costs add a total of 3.0 billion, bringing the total Capital Costs to 17.9bn (PV, 2009 prices)

95 Chapter 10: The Overall Business Case for HS2 HS2 Operating and Maintenance Costs As outlined in the HS2 Cost and Risk Model (see table in paragraph 5.1), the annual maintenance and operating costs for the track is estimated as 180,000 per route kilometre. Optimism bias of 41% is applied on top of this, giving total annual track operation cost of 46 million. Over 60 years and in market prices this amounts to 0.8 billion (PV, 2009 prices) The same table summarises operating and maintenance costs for the four stations forming part of HS2. The total 2009 PV of maintenance and operation costs for stations is almost 400 million The service specification of HS2 implies a total of around 102,000 train kilometres a day. This is a combination of 85,000 km served by 200 m long classic compatible trains and around 17,000 km served by either 200m or 400m high speed captive trains. Demand for High Speed services to Birmingham is estimated to be sufficiently strong to justify running 400m trains for some time of the day. As set out in section 3.6, we have modelled more 400m trains to ensure a better representation of capacity and crowding in the model. However, for the purposes of our cost calculations we have assumed that 50% of services between London and Birmingham would operate two train sets To convert the daily service pattern to an annual supply total, a factor of 350 has been used. This was estimated comparing weekday to weekend service patterns on the WCML between London and Birmingham. Applying the maintenance rate set out in section 5 of HS2 Cost and Risk Model and allowing for 41% optimism bias brings the annual stock maintenance costs to 180 million. The 60 year PV at market prices is 3.3 billion Turning to train operating costs, the cost and risk model quotes the traction power component as Adding staff and other costs means the total per km operating costs for a 200m train are Given that a 400m train does not need two drivers, the operating costs are less than double that of a single set, at per km (we ignore the small reduction to traction power) Allowing for 41% optimism bias, the total annual train operating costs amount to around 220 million. As a 60 year PV at market prices, this represents 4.0 billion (PV, 2009 prices). 95

96 HS2 Demand Model Analysis Classic Rail Savings Most of the services specified to run on HS2 are replacing classic rail services on the West Coast Main Line (WCML). While some of the released capacity is being re-used for local services, the introduction of HS2 would result in some operating cost savings on the WCML. Our modelling of how released capacity might be used to best reflect demand patterns has not been optimised. However, we estimate that the net reduction in train km for Pendolinos would be around 5 million km a year while the additional services specified for Desiros would be approximately 3 million km a year We have used the variable cost module of DfT s Network Modelling Framework (NMF) to estimate the total variable costs per train km for the types of rolling stock involved based on the NMF s 2020 forecast. The net annual saving would be estimated as slightly over 50million. Over 60 years, and in market prices, this amounts to a total saving of just under 1 billion (PV, 2009 prices). HS2 Appraisal Cost Summary Table 10.3 below summarises all the cost items discussed above. Table 10.3 Summary of HS2 Costs Capital Expenditure billion (2009 prices) Construction 13.7 Rolling Stock 3.0 Renewals 1.1 TOTAL Capital Costs 17.9 Operating & Maintenance Track 0.8 Stations 0.4 Train Maintenance 3.3 Train Operation 4.0 Classic Line Savings -1.0 Total Operating & Maintenance Costs 7.6 TOTAL COSTS (PVC)

97 Chapter 10: The Overall Business Case for HS Appraisal of Benefits from HS Our appraisal of benefits is based on, and consistent with, DfT s WebTAG appraisal guidance. Estimates of generalised costs from the HS2 demand model are used to calculate the benefits to transport users, and changes in the number of car vehicle km and air passenger movements are used to estimate the value of other impacts such as accidents, air quality and noise for which there are established monetary values A high speed line would offer benefits from faster, more reliable, more frequent and, in many cases, less crowded services. On this basis we estimate that HS2 would generate benefits of some 32.3bn (PV) and increase net rail revenues by almost 15bn over the course of the 60 year appraisal period Almost 90% ( 28.7bn) of these benefits come to transport users. These benefits are driven by time savings and improved reliability offered by HS2. These are worth over 13bn in total. HS2 would also deliver some 5bn of benefits through reduced crowding. This includes almost 800m of reduced crowding on short distance trips in the South and Midlands as a result of re-use of capacity freed up on the WCML. The remainder of the benefits to transport users come from reduced waiting time and improved access to stations, as well as benefits to road users of lower congestion These benefits are spread across much of the UK. The three largest economic centres in the country London, Birmingham and Manchester representing almost a quarter of the UK s employment, would benefit directly from the scheme. In particular connectivity between these cities would be significantly improved. The benefits would not be limited to areas directly served by HS2. Passengers from a wide catchment would be likely to access high speed services, using both road and classic rail to access the high speed stations Around two thirds of the benefits come from people using the classic compatible services to and from places further north than Birmingham. Figure 10.4 below shows the distribution of benefits according to where trips start. Of course where a trip starts may not represent where the benefits are experienced, but it provides some indication of who will gain as a result of HS2. 97

98 HS2 Demand Model Analysis Figure Benefits of HS2 by Origin of Trip in

99 Chapter 10: The Overall Business Case for HS Figure 10.4 shows that the benefits of HS2 accrue all along the line of the WCML. Trips starting in London, Birmingham, Manchester, Glasgow and Liverpool drive much of the benefits, reflecting the major centres of population and economic activity. However the benefits stretch all along the WCML, and are particularly clustered around stations which will be served by HS2 Classic Compatible trains, including Warrington, Preston and Crewe. Table Benefits of HS2 by Region and Purpose Regional User Benefits Business Other London 36% 36% South East 6% 5% West Midlands 19% 18% North West 22% 22% Scotland 8% 7% Other 11% 11% Table 10.4 above gives the regional breakdown of benefits to long distance trips starting in different regions (looking at the benefits according to where a trip finishes would give a similar pattern of benefits). Trips starting in London and the South East account for the largest share of benefits and there are significant benefits from trips starting in the West Midlands. Around one third of the benefits accrue to trips starting north of Birmingham with the North West the biggest beneficiary Business passengers would gain the most value from HS2, representing over 60% of the benefits. This is despite representing only around 30% of trips and largely reflects the high value that business users and their employers attach to having faster journeys. Other users of HS2 would also gain significantly from improved journey times, reliability, and relieved crowding delivering benefits worth over 11bn. Benefits by Transport Mode As would be expected, the benefits would not be spread evenly across the transport modes as the vast majority of benefits are experienced by the HS2 passengers themselves. HS2 Passengers. These gains are mainly driven by improved journey times, with reliability and reduced crowding also generating significant benefits. Passengers on the Classic Line. Taking long distance journeys onto HS2 would free up capacity on the WCML. This would reduce crowding substantially and greater frequency would be offered on local and regional services where appropriate. Re-use of capacity by short distance services would be expected to deliver benefits of around 2-4bn. Road Users. Around 11,000 long distance car trips would be likely to transfer to HS2. This would lead to a reduction in congestion but the net impact of this is relatively small. For example traffic flows on the southern section of the M1 would fall by around 2%. However across all road users, this adds up to some 2bn in benefits. 99

100 HS2 Demand Model Analysis While the majority of transport users would benefit from the introduction of HS2, some passengers could experience longer or less frequent services particularly those on the GWML who would have an extra stop at Old Oak Common or people travelling from some stations on the WCML. Also some services could see increased crowding with more passengers using rail and underground services to connect to high speed services. These impacts and the disbenefits they generate are outweighed by the large benefits to be gained by HS2, and might also be minimised by further detailed development of the classic rail timetable and train service specification Wider Economic Impacts of HS The benefits of HS2 considered so far have mainly been those traditionally estimated in transport appraisal such as time savings, crowding and reliability. There is an increasing volume of evidence that transport interventions can generate further benefits, mainly to the productivity of the economy. These Wider Economic Impacts (WEIs) include the benefits from improved linkages between different firms and between firms and their workers, which can lead to economies of scale, and other efficiencies. Further potential impacts may be realised if HS2 results in changes in the spatial pattern of economic activity in the UK DfT has been developing a methodology to assess the first of these WEIs for a number of years. Guidance is due to form a part of the Department s WebTAG guidance on appraisals from next year and as such will form a requirement for appraisals to assess these impacts. The new methodology addresses the questions of benefits arising from the consequences of market imperfections concentrating on the net monetary benefits to the economy as a whole that are not captured in Transport Economic Efficiency analysis. There are three broad components of these benefits: Agglomeration Benefits. These are the benefits of improved linkages between firms. Labour Market impacts. These are mainly derived from benefits to commuters which may encourage more people into the labour force, or encourage those who already have jobs to work more. This will boost the level of productivity in the economy. A further possible impact people moving to more productive jobs has not been explicitly calculated by HS2 as this requires modelling of land use change. Imperfect competition. This impact reflects the fact that in a world of market imperfections, increases in production (output) will lead to benefits since consumers value the extra goods and services by more than the costs of production. This leads to further benefits not captured in conventional appraisal. 100

101 Chapter 10: The Overall Business Case for HS In many cases, it is increases in agglomeration which offer the most significant benefits. The model of agglomeration which DfT use is based on the potential spillover effects from the increased proximity of firms (either through lower cost or faster transport between those firms). Improving accessibility within a city making firms closer together leads to agglomeration benefits (improvements in productivity). However the scale of this impact falls the further apart firms are so reducing journey time between two firms from 1 hour to 40 minutes will have little impact, while reducing it from 30 minutes to 10 minutes will have much larger impacts In this sense HS2 would seem to deliver limited agglomeration benefits since the scheme (on its own) would do little to improve accessibility within a city. And recent evidence on the decay function suggests firms in London and Birmingham would remain too far apart even with high speed to enjoy significant agglomeration benefits. In addition, whilst better access to work opportunities can lead to improvements in the operation of the labour market (the more people in work effect), it seems unlikely that the levels of commuting over HS2 itself would be sufficient for this to be a significant source of benefits There would still be some benefits, particularly from the potential use of released capacity on WCML to improve commuting services into London and Birmingham, as well as some road decongestion benefits. However the initial view of these impacts is that they would not add significantly to the business case HS2 and a wider HSR network would nonetheless represent a step change in connectivity between cities. We need to be confident that the approach developed by DfT (which is focused on connectivity within cities) captures all of the wider impacts of HSR. For this reason HS2 has also considered two further aspects of Wider Economic Impacts: Inter-city connectivity considering both theory and evidence that transport investments may have agglomeration impacts over a wider area. The potential for land use change to drive benefits at local, regional and national levels. Applying WebTAG Guidance - Wider Economic Impacts Table 10.5 provides a summary of both the traditional appraisal impacts and the additional Wider Economic Impacts, as estimated using this draft guidance. 101

102 HS2 Demand Model Analysis Table Benefits of High Speed 2 Using DfT s Transport Appraisal and Wider Economic Impacts Guidance Benefits Welfare ( m) A) Conventional Appraisal Time Savings (including crowding) Business user savings 17,600 Commuting & Leisure user savings 11,100 Other Benefits Other User Impacts (Accidents, Air Quality, Noise) 44 Total transport user benefits - conventional appraisal 28,700 B) Wider Economic Impacts Labour Market Impacts Increase in labour force participation 0 People working longer 0 Move to more productive jobs Not Included Exchequer consequences of increased GDP 0 Agglomeration benefits 2,000 Increased competition 0 Imperfect competition 1,600 Additional to conventional appraisal 3,600 C) Total (excluding financing, social & environmental costs & benefits) 32,300 All in m, appraised over 60 year time period, discounted to 2009 values, 2009 prices Section A of table 10.5 summarises the results of the more conventional appraisal of transport user benefits outlined in WebTAG. These have been described in more detail in the previous section. Section B outlines each of the components of Wider Economic Impacts that represent additional benefits, as calculated using the draft guidance from DfT Calculating Wider Economic impacts is not clear cut for such a large infrastructure project as HS2. Labour market impacts are minimal since HS2 is unlikely to benefit significant numbers of commuters. The opportunity to move to more productive jobs may be more significant but we have not been able to consider it systematically in the time available although we note the potential of land use change below. 102

103 Chapter 10: The Overall Business Case for HS There are also challenges to applying the guidance on agglomeration to a transport model which has greatest detail in long distance rail trips, when most agglomeration impacts are driven by short distance (and often car) trips. The HS2 model is not a local highway model, it focuses only on long distance trips (with short distance trips pre-loaded onto the road network). As a result we have had to use various different approaches to estimate the agglomeration benefits of HS2. Our central estimate suggests benefits of around 2bn, within the range of 1bn and 4.5bn. A further 1.6bn in benefits occurs as a result of increasing output of imperfectly competitive markets Overall we estimate Wider Economic Impacts based on DfT s draft guidance would add a further 3.6bn (11%) to the benefits of HS2 (within the range 2.6bn to 6.1bn). Inter-city Connectivity The existing DfT guidance focuses on the role of transport in improving connectivity within an agglomeration or region. However HS2 will fundamentally improve connectivity between regions and cities and may have different impacts. There are also some indications to suggesting spillover effects from investments over a far large distance than those suggested by DfT s distance decay functions We asked Daniel Graham and Patricia Melo (from the Centre of Transport Studies, Imperial College London) to consider the potential for further benefits, and to confirm whether these are additional to the more traditional benefits measured in transport appraisal. The aim of the study was not to quantify potential impacts, but to look at what mechanisms of agglomeration (from existing theory) might work over longer distances, consider whether they exist and whether they are significant in scale. The results of this work are detailed in a separate paper, but broadly suggest: The theory of agglomeration does not preclude the generation of externalities over wider distances (and specifically between key cities). These would be driven principally by labour market effects and knowledge spillovers. Empirical studies estimating the spatial distribution of agglomeration effects consistently find evidence of sharp decay. However, results also show that smaller agglomeration effects can be available over longer distances. For instance, Rosenthal and Strange (2008) 16 find significant effects up to 100 miles (160 kilometres), while Rice et al. (2006) 17 find that the impact of economic mass is still statistically significant up to 80 minutes driving time from source. For HS2, agglomeration effects are likely to be relatively small overall, and particularly in relation to the transport user benefits While this suggests there may be some additional benefits that are not included in our estimates of wider economic impacts, it is unlikely that they will change the conclusions presented in this report. 16 Rosenthal, S. and W. Strange (2008). The attenuation of human capital spillovers: a Manhattan skyline approach. Journal of Urban Economics, 64, Rice, P., A. J. Venables, and E. Patacchini (2006). Spatial determinants of productivity: analysis for the regions of Great Britain. Regional Science and Urban Economics 36,

104 HS2 Demand Model Analysis Land Use Change We have also considered the impacts of changes in spatial patterns of economic activity that might result from HS2. These could include firms relocating to take advantage of the new high speed line. There are many examples where there have been substantial changes in the structure and land use of cities served by HSR. For example: Lyon has seen the virtual relocation of its commercial district to the area around the TGV station Lille has had significant success in regenerating the area around the TGV station, with businesses attracted to the strong international links However the benefits of such changes (and particularly whether they can be added to an appraisal) are less clear. We have been unable to undertake significant research in this area, and to do so would probably have needed a level of detail in both design and policy that would not have been appropriate at this stage. However we have reviewed some of the international experience and literature, as well as drawing heavily on the experience and knowledge of Roger Vickerman (Professor of European Economics and Dean of the University of Kent at Brussels) and Reg Harman (Interfaces) A more detailed summary of the findings of this work can be found at Appendix 3. However the conclusions of this review can be summarised as: Integration is Key. Simply building a station or link to the high speed network is not enough. For success to be achieved the station has to be integrated in to the local transport network, but perhaps more importantly integrated into the wider strategic plans of local agencies. Wider Strategies. As the Eddington Study identifies, there are many factors which are more important in regeneration than transport alone. It not surprising therefore that wider strategies on land use planning and even education and skills may be needed to successfully integrate a station into the local economy and ensure that potential benefits are realised. Role as a hub. Whilst not always the case, there are examples of success where the high speed rail station also has hub-like connectivity with good links to the local/regional rail network as well as the high speed network. Thus the station becomes a focus for the regional economy as well as a wider market supported by high speed. This is not all win-win. Although there are many examples where growth and regeneration has been delivered around a high speed rail station, this may be to the detriment of the surrounding region The evidence suggests that HSR has the potential to deliver significant benefits for local and regional economies. However it is not clear that this leads to significant impacts at the national level with many jobs simply being displaced from other areas. 104

105 Chapter 10: The Overall Business Case for HS Our conclusions from this work suggest that during the course of designing HS2, it will be essential that the scheme is not treated purely as a transport scheme but is integrated into local and regional strategies. However, whilst HS2 has the potential to have significant local and regional impacts, the impact on national productivity is less clear. Summary The evidence we have seen suggests that, overall, wider economic impacts are likely to be a relatively small part of the business case for HS2 at a national level (adding perhaps 10-15% to the benefits). However at a local level the impacts could be much more significant. There is evidence from around the world of high speed rail stations supporting the growth, regeneration and even relocation of urban centres. Locating a high speed station at Old Oak Common, for example, could be a catalyst for the development of other rail links and with them improved connectivity and regeneration Such growth would not flow automatically from the provision of a new station. In order for successful change to be delivered the detailed design of stations in London and Birmingham would need to make sure that they include: Integration of the high speed network within the long term vision of the city being served. A new service ought to be actively supported by other policies to improve the local economy. Integration with the local transport network. Strong local leadership to drive change and take account of local needs HS2 would also be one of the largest construction projects ever undertaken in the UK, with the potential to create up to 10,000 construction jobs, and a further 2,000 permanent jobs through maintenance and operation Impact of HS2 on Carbon Emissions The assessment of the impact of HS2 on carbon emissions is covered in the Appraisal of Sustainability (AoS), and was conducted by Booz and Temple Group using data provided from the HS2 demand model. However we have also undertaken further calculations of carbon implications to help us to better understand the sensitivity of these results to key assumptions and the implications for our conclusions. The results are all set out in the Appraisal of Sustainability and the HS2 Report. However for completeness we report here the methodology used to underpin the analysis that we have conducted The conclusion of our analysis, and that presented in the AoS is that HS2 is unlikely to have a significant impact on overall emissions from transport. There is significant uncertainty surrounding the impact, and the assessment is particularly sensitive to assumptions around the carbon intensity of electricity and the response of the aviation industry as a result of HS2. However even taking this into account, we estimate HS2 will result in somewhere between a small (0.3%) increase in transport emissions through to a small (0.3%) decrease. Given the range of uncertainty and the likely small impact of HS2 we have not quantified the value of carbon emissions in the business case. 105

106 HS2 Demand Model Analysis Emissions from Rail The impact of HS2 on rail emissions is three fold: There would be an increase in emissions as a result of HS2 trains consuming electricity There would be a reduction in the number of Pendolinos on the WCML, as these trains are replaced with HS2 trains However the additional trains used on the released capacity would result in additional emissions from both electricity, and a small number of diesel trains The energy consumption of HS2 trains has been modelled explicitly using information on the line of route including speeds and acceleration patterns, gradients, tunnels. A train running along the length of the line consumes around 4.4MWh (Megawatt hours), which is equivalent to 25 KWh (Kilowatt hours) per km For classic compatible trains running beyond the high speed line, their performance is assumed to be comparable to that of a 9-car Pendolino. A recent energy metering trial suggests this is equivalent to 14.3KWh per train km. This suggests that HS2 trains both HS captive and classic compatible fleets - will consume just over 850GWh (Gigawatt hours) per year. To offset this, we estimate there would be a reduction of around 5.4m train kilometres travelled by Pendolinos, saving some 77GWh per year To convert this to carbon emissions requires an understanding of the carbon intensity of electricity. This is a key assumption, but is also highly uncertain. The carbon intensity currently stands at just over 0.5kgCO2 per KWh. However it is expected to decline significantly in the future. Government projections suggest it should fall to just under 0.4kgCO2 per KWH by 2025, but beyond this there is no firm commitment In practice carbon intensity is likely to fall further if the UK is to achieve its targets on climate change. The Committee on Climate Change has suggested it will need to fall to less than 0.1kgCO2 per KWh by 2050 to achieve the targets set out in the Climate Change Act. However since this is not current government policy we have been relatively cautious in our central case. We have applied a factor of 0.385kgCO2 per KWh, but have applied a wide range to this assumption. The upper bound is today s emissions levels, but at the lower bound HS2 could (at least in theory) be supplied entirely from renewable sources. This is likely to be an extreme assumption but is the theoretical limit of emissions. 106

107 Chapter 10: The Overall Business Case for HS On the basis of these assumptions we estimate HS2 trains will emit around 0.33 MtCO2 (Million tonnes of Co2) per year (within the range 0 to a 0.43MtCO2 increase in emissions per year); The reduction in Pendolinos will save 0.03MtCO2 per year (within the range 0 to a 0.04 MtCO2 saving per year); The re-use of capacity will increase emissions by 0.02 MtCO2 per year (within the range of an increase of 0.01 to 0.02 MtCO2 per year) The increase in emissions from trains used for released capacity has been estimated using data from DfT s NMF model which estimates the average emissions per km of electric and diesel trains on the classic network. This does not as standard report energy consumed, but has been adjusted to allow different assumptions on carbon intensity of electricity. At the current level of carbon intensity of electricity, this model suggests the average train emits just over 5kgCO2 per train km, which forms the starting point for the range of impacts above. Mode shift from road HS2 would deliver a reduction in road journeys, particularly on key routes from Birmingham and Manchester. Our demand model estimates there will be almost 22 million fewer car km in 2033 as a result of HS2. This could reduce carbon in two ways: The reduction in car trips results in a direct reduction in emissions as that journey is undertaken on HS2; Reduction in congestion speeds traffic up, which would have an indirect effect on cars that remain on the road network. This generally improves fuel consumption (and reduces emissions), although in some cases the opposite is true We have not calculated the impact of the latter. Given the scale of change in road km (less than 1% of all car km in 2008), congestion effects are unlikely to have significant impacts on fuel efficiency WebTAG provides estimates of fuel consumption depending on the mix of cars (petrol/diesel) and the speed the car was travelling at. This can be converted into a range of emissions per car km ranging from 0.4 kgco2 per km at low speeds, through to 0.16 kgco2 per km at just over 60mph. This means the reduction in carbon emissions as a result of mode shift from car is within the range MtCO2 to MtCO2 per year. 107

108 HS2 Demand Model Analysis Mode Shift from Air The impact of mode shift from air is the single biggest uncertainty in our estimates of carbon emissions. The HS2 demand model suggests that HS2 would lead to around 11% fewer domestic air passengers. However this in itself does not deliver a reduction in carbon emissions. It is how the airlines respond to this change in demand that would determine the impact of HS2 on aviation emissions Airlines could respond by reducing service frequencies, or flying smaller planes. They could even respond by withdrawing routes altogether, perhaps with the opportunity of code sharing with HS2 (as, for example, Air France do on routes to Brussels). Alternatively they might not respond at all choosing to maintain current service levels in order to maintain a service for interlining passengers (who tend to be higher value customers for airlines) We have estimated a range of emissions reductions based on: Airlines respond by reducing the size of planes and frequencies such that emissions per passenger are maintained. Thus the 11% fall in air passengers would reduce domestic aviation emissions by the same proportion. Based on data of domestic aviation emissions 18 this is equivalent to a reduction of around 0.4MtCO2 per year in Airlines do not respond at all, and there is no reduction in aviation emissions as a result of HS We have not considered in this range the potential for airlines to re-use slots freed up at airports as a result of a reduction in the number of domestic flights. If airports slots are re-used for flights to new destinations, then this would have implications for the emissions from aviation. Summary of HS2 Carbon Impact The impact of HS2 on UK carbon emissions is uncertain, and highly dependent on assumptions of the carbon intensity of electricity which the scheme uses, and of the response from airlines to changes in passenger numbers as a result of HS2. Despite this, it would seem that the impact of HS2 on UK carbon emissions is likely to be small. We estimate that this impact is equivalent to a range of -0.3% to +0.3% of all UK transport emissions. Our central estimate is a net reduction in emissions of less than 0.1MtCO2 (less than 0.1% of UK transport emissions). This suggests HS2 would not be a major factor in managing carbon in the transport sector. 18 Taken from UK Aviation: Carbon Reduction Futures DfT (2009) 108

109 Chapter 10: The Overall Business Case for HS HS2 Value for Money Overview In the preceding sections we have outlined the substantial benefits as well as costs of HS2. In this section we draw this together to consider the strength of the overall business case, and whether the benefits justify the costs. Table 10.7 summarises all of the key impacts that can easily be quantified and valued in monetary terms. Table 10.7 Appraisal Summary Table of HS2 Quantified Costs and Benefits of HS2 (PV 2009 discount year and prices) (1) Transport User Benefits Business 17.6bn (2) Other Benefits (excl. Carbon) Less than 0.1bn Net Transport Benefits (PVB) (3) = (1) + (2) 28.7bn (4) Wider Economic Impacts (WEIs) 3.6bn Net Benefits incl WEIs (5) = (3) + (4) 32.3bn (6) Capital Costs 17.8bn (7) Operating Costs 7.6bn Total Costs (8) = (6) + (7) 25.5bn (9) Revenues 15bn (10) Indirect Taxes - 1.5bn Net Costs to Government (PVC) (11) = (8) (9) (10) 11.9bn Other 11.1bn NATA BCR (12) = (3)/(11) BCR with WEls (13) = (5)/(9) The net transport benefits (shown as item 3 in the table) would be worth almost 29bn. Benefits to business and other transport users make up the bulk of this ( 17.6bn and 11.1bn respectively), with small further benefits (less than 0.1bn) from reductions in accidents, noise and air pollution from lower road traffic. A further 3.6bn could be added through Wider Economic Impacts (item 4). This means the total benefits of the scheme are estimated to be 32.3bn 109

110 HS2 Demand Model Analysis Against these benefits, the costs of high speed two are substantial. Over the 60 years of an appraisal, costs would be almost 25.5bn. The bulk of these are capital costs ( 17.8bn). The remainder (about 30% of costs) are the net impact on operating costs, covering both HS2 trains and the classic network DfT consider the value for money of a scheme in terms of the value of benefits per pound of Government spending. The cost of the scheme is not the same as Government spending since increasing revenues on the rail network (worth 15bn) would offset the costs. Changes in indirect tax revenue also need to be accounted for here. HS2 would reduce these revenues by 1.5bn as a result of a reduction in the number of long distance car trips. The net cost to Government would be 11.9bn The Benefit Cost Ratio (BCR) is the net benefits divided by this net cost to Government. On this basis the BCR would be 2.4. Adding in the Wider Economic Impacts generated by HS2, the BCR increases to 2.7. This means the scheme would deliver 2.70 in benefits for every 1 spent by Government. 110

111 Chapter 11: A Long Term Strategy for High Speed Rail

112 HS2 Demand Model Analysis 11.1 Introduction This chapter describes the work underlying the recommendations on the development of a high speed line beyond the West Midlands as set out in chapter 6 of the main report. We have looked at three possible configurations for full high speed networks as well as addressing the question of possible next steps following the London to West Midlands line In order to meet these two objectives, we have approached them from different analytical directions. For the wider network question, we have started from a blank sheet, essentially assuming the entire network was built at once. What we have assessed here are the benefits from new high speed services (mainly on a dedicated high speed network). We have not attempted to optimise the use of the new infrastructure which would in large sections be used below capacity. For these tests we assume classic rail services are unchanged from a world without any high speed rail The basis of these tests is necessarily strategic. We have not sought to optimise network designs or service specifications. Instead the tests provide a high level assessment of the case for a wider high speed rail network, as well as a comparison of the relative strength of the three configurations that we have considered The question of extending HS2, however, required us to start from the central case for HS2 outlined in Chapter 10 (henceforth Day One scenario). In these tests covering possible extensions of HS2 to Manchester and to Leeds we were interested in the incremental benefits of extending HS2, and so the tests had to be consistent with the Day One scenario. This means time savings are incremental to those delivered on Day One where classic compatible services would already deliver significant time savings to Manchester, Liverpool and Glasgow, as well as improved reliability. Classic rail services are assumed to be the same as in the Day One scenario, including the re-use of released capacity on the WCML. All these aspects add significantly to the direct benefits of providing high speed services between London and Birmingham. The different starting points for these tests mean they cannot be directly compared to the results of the wider network tests The remainder of this chapter starts with an outline of the markets that the wider network would be serving. From there it moves on to summarising our approach to analysing the three full networks in demand modelling terms before the results of this are presented in the third part. The final section discusses the implications for potential next steps, the possible increments on a high speed line to the West Midlands. 112

113 Chapter 11: A Long Term Strategy for High Speed Rail 11.2 Long Distance travel in Great Britain This section briefly presents the market for long distance travel in Great Britain and sets out the context for analysing a high speed network. It concludes with a description of the three full networks that we chose to analyse Our remit asked us specifically to look at the potential for high speed rail to serve three of the largest English conurbations Greater Manchester, West Yorkshire, and the North East and Scotland. To these we also added the East Midlands and South Yorkshire, both of which potentially lie on an easterly line of route towards Yorkshire. Scotland 5.1m They are major centres of populations, exhibiting significant passenger flows to and from London on today s conventional rail network. Together, the regions which support these conurbations account for over 60% of the total English population, with Scotland adding a further substantial market The remit focused on the potential extension of the core HS2 route to form a wider network, and as such did not include links to other conurbations in the South, South West and East of England or South Wales which would not form natural extensions of HS2, but rather require wholly separate high speed lines out of London. So while these lay outside the scope of our work in 2009, this is not to say that they may not be justified We undertook some early high level analysis based on existing long distance flows between main cities within our remit to identify where the main demand for long distance rail travel lies. Table 11.2 shows the daily trips to or from London to the major cities in the UK (from Planet Long Distance base year). North West 6.8m North East 2.5m West Mids 5.3m Yorks & Humber 5.0m East Mids 4.5m London 7.4m Source: ONS popluation estimates,

114 HS2 Demand Model Analysis Table 11.2 Population and Long Distance Demand to London in 2008 Primary Urban Area (PUA) PUA Population (000) Daily Return Trips to Inner London Rail Highway Air Milton Keynes 219 4, Birmingham 2,279 4,296 1,458 0 Manchester 1,760 3, Northampton , Oxford 144 2, Leeds 729 2, Nottingham 610 1, Leicester 431 1, Newcastle 802 1, Liverpool 765 1, York 187 1, Coventry 304 1, Sheffield 769 1, Edinburgh Preston Derby Doncaster Glasgow 1, Stoke Flow from PUA overestimated (PLANET zone larger than PUA) The flows from Milton Keynes, which is relatively close to London, are dominated by commuting trips. Our work on intermediate stations (see Chapter 6) suggests that while such markets may generate benefits for local passengers the impact on wider HS2 passengers, as well as the impact on capacity of the most heavily utilised part of the network, means they are unattractive. Birmingham, Manchester and Leeds have the highest demands for cities further than 150km from London and produce the most passenger kilometres. 114

115 Chapter 11: A Long Term Strategy for High Speed Rail Flows from Edinburgh and Glasgow appear to be less strong; however a new high speed line would represent a step change in connectivity which might significantly increase demand. Both stations could also provide access to travellers from wider Scotland and could create a strong competitor to air passengers, which adds to the potential market for high speed rail. For those reasons, both stations were taken forward for consideration The case for a further network is not simply limited to links to London; links between other cities may be important and drive additional demand on HS services. Analysing the existing flows highlighted significant cross-country demand between Glasgow and Edinburgh with around 14,000 daily return trips as well as on the corridor between Liverpool, Manchester and Leeds This analysis suggested a number of key cities for a wider network within the constraints of our remit and consistent with emerging thoughts on potential lines of route. These were Birmingham, Manchester and Leeds with additional potential for stations around Newcastle, Sheffield and within the East Midlands as well as Scotland. We did not include Bristol, Cardiff or Brighton, which are clearly outside our remit Long distance travel is forecast to triple by 2033: there would be more than 7 million trips per day that exceed 50 miles across the regions under consideration here. Out of those, around 5m trips would be intra-regional (start and end within the same Government office region). Of the remaining 2 million trips per day, 360,000 (or 15%) either start or end in London. Looking only at air and rail modes, we forecast about 500,000 daily inter-regional long distance trips by 2033, out of which 270,000 or 56% involve London at either end. 19 5,000 to 6,000 daily returns between Manchester and Leeds Liverpool to Manchester is less than 50miles, thus no long distance trips are shown, nevertheless flows are significant. 115

116 HS2 Demand Model Analysis 11.3 Long Term High Speed Networks We have identified three possible national network configurations that would cover these markets to varying degrees. These are outlined below. All three build on the preferred scheme for HS2 between London and the West Midlands. We have not fully optimised these networks but have developed them to help understanding the relative merits of different basic approaches. An Inverse A Configuration The Inverse A configuration is an adaptation of networks which have been examined in past studies. It is the most comprehensive network that could be supported by the capacity of HS2, relying as it does on one route north from London The Inverse A aims to maximise benefits to the widest number of people by offering direct London access to each of the conurbations in our remit, as well as Merseyside (via the existing classic line), East Midlands and South Yorkshire. The transpennine link between Manchester and Leeds would carry only east-west flows, with services to and from London travelling either side of the Pennines. This configuration would also unlock potential for a network of high speed inter-regional services. 116

117 Chapter 11: A Long Term Strategy for High Speed Rail A Reverse S Configuration Similar network configurations have also formed the subject of investigation in the past. The network provides connections to all the major conurbations detailed in the remit, using a linear route which would minimise the total amount of construction. Under this scenario, all trains north of Manchester would need to cross the Pennines. This would increase journey times between London and Leeds, Newcastle and Scotland, compared to the alternative configurations In Scotland a number different permutations exist for serving Edinburgh and/or Glasgow. In each of the configurations, we assume separate legs serving Edinburgh and Glasgow and have not modelled the benefits of a link between the cities. 117

118 HS2 Demand Model Analysis A Reverse E Configuration The Reverse E configuration builds upon HS2 to the east of the Pennines. Unlike the Inverse A and Reverse S configurations, this network does not extend from the northern limit of HS2, which would remain connected to the West Coast Main Line Because HS2 extends beyond Birmingham, the best journey times to Manchester and Liverpool under this scenario would remain those achieved with classic-compatible HS2 trains, running on the West Coast Main Line. The purpose of the high speed connections to Manchester and Liverpool would be to enhance regional links across the Pennines, but we have not modelled this Such a line could also be used to achieve better high speed journey times to the North West but only with a more central alignment of HS2 (towards Leicester rather than Birmingham). However, this would rule out a Heathrow connection, entail longer journey times to Birmingham, and compare poorly with journey times to the North West in the Inverse A. With a more central alignment of HS2, the Reverse E would become more akin to the proposal put forward by the 2M group of London Councils (known as High Speed North ). As our remit was to consider the development of HS2 beyond the West Midlands, we have not investigated the 2M proposals in detail. 118

119 Chapter 11: A Long Term Strategy for High Speed Rail 11.4 Wider Networks - Modelling Approach Given the strategic nature of this work, we have taken a cautious approach to the modelling in terms of taking broadly conservative assumptions on benefits and using high end estimates on costs. This section starts by setting out some general modelling assumptions specific to the analysis of the wider networks. The text then describes our thinking on journey times and service patterns for the individual networks and especially on the importance of London bound journey times. Modelling assumptions for the three strategic networks In order to model the maximum capacity a new line could support we have assumed 400m trains to be used for every route and throughout the day. This reduced the need for model runs by minimising the crowding impacts, and so maximising the potential benefits of the service specifications modelled. In the real world, demand on some routes and/or during some periods might be weaker so 200m trains would be sufficient. This could lead to savings in operating costs though it might also impact on the benefits reported in this document Similarly we have not endeavoured to re-design the classic railway services for this strategic review as we have done for HS2. Instead we assume an entirely new high speed network with classic rail services continuing as in the reference scenario. We have also not tested the implications of the limited number of hybrid services on the existing trains running on the classic line (in the Reverse E and Reverse S) The tests of the wider network configurations also ignore the potential for high speed rail to deliver reliability improvements over the existing classic network. Nor have we considered the potential for wider economic impacts that a comprehensive high speed network might deliver Outside London and the West Midlands, the demand model is of a strategic nature and lacks the granularity required to model in detail the access and egress to newly designed high speed rail stations. We have instead used existing stations with their local accessibility settings as they exist in the Planet Long Distance model Compared to our approach to appraising the line to the West Midlands, most of these assumptions will result in a more conservative estimate of the business case for a full network. Optimisation of the business case may find opportunities for cost savings and changes to the benefits. Generally this analysis provides a robust indication of the relative strengths of the business cases for each of the networks considered, but all could be refined further with more detailed design work. 119

120 HS2 Demand Model Analysis Importance of Journey Times to London Following on from the analysis of existing long distance flows referred to above we used an early version of the demand model, to estimate the potential merits of the three network designs as well as various sensitivity tests on the Inverse A. These runs used notional, but realistic, service patterns The model outputs were used to analyse the marginal benefit of additional trains (and thus higher frequency) or faster journeys between the various destinations. The aim was to provide an overview of the key factors driving the business case frequency against faster journeys; which stations were the most important for delivering benefits The results of this analysis highlighted the importance of London flows as opposed to cross-county trips: it suggested that travellers get larger benefits overall from faster journeys to and from London rather than from more frequent, stopping services that also connect stations outside London to each other. With this insight, we adjusted our initial service specifications so that there were fewer stopping services and more faster, more direct trains to London. While some destinations have fewer trains per hour, most places gain significantly due to the faster journey. Details on the modelled service patterns are contained in Appendix While we believe the final service specifications represent a credible, realistic base for comparing the different network configurations at this strategic level, more iterations of this type of optimisation process could identify changes that could improve the use of the available track capacity further The main difference between the Inverse A and the Reverse E configuration is that in the latter high speed trains to Manchester would need to run via the East Midlands and South Yorkshire. Compared to the hybrid services connecting London to Manchester via the HS2 on Day One, no further time saving would be achieved. The modelling therefore assumes the day one services to continue in this scenario. The Reverse S does not serve the East Midlands and South Yorkshire (and so misses many of the benefits for passengers in these areas) Compared to the Inverse A, the London to Scotland services are half an hour slower in the E and slightly more so in the S. Newcastle and the North East benefit from some of the Scotland services stopping there under the E and the S, which offers some compensation for the slower journey times. 120

121 Chapter 11: A Long Term Strategy for High Speed Rail 11.5 Demand and Benefits of a Long Term Strategy Of the three networks, the Inverse A offers the best business case. It is the most extensive of the networks and thus has the highest costs. The benefits and revenues from a wider coverage and faster journeys to and from London, however, more than compensate for this, leading to a higher ratio of benefits to costs (BCR) than either the Reverse E or the Reverse S This section first covers in some detail the results from the demand model in terms of demand and revenue as well as benefits. A brief summary of the costs follows before the third section brings the two together into the BCRs. A final section discusses the main caveats and limitations of the current work. Demand With over 440,000 daily passengers forecast to use high speed services in the Inverse A, this configuration clearly creates the highest demand. The total flow on the Reverse E would be just over 400,000 or nearly 10% less. The Reverse S would attract about a fifth less than that, around 325,000 trips per day in Table 11.5a shows trips to and from London which account for roughly half of the total ordered by the region in which the trip starts or finishes. Table 11.5a Daily High Speed Rail Demadnd to and from London with a wider HSL network Daily HS2 Demand to/from London Inverse A Reverse S Reverse E Scotland 43,000 40,000 38,000 North East 24,000 22,000 23,000 North West 53,000 51,000 43,000 Yorkshire & Humberside 39,000 26,000 38,000 West Midlands 39,000 39,000 39,000 East Midlands 20,000 3,000 20,000 Total 219, , , The Reverse S does not serve the East Midlands, so has only a minimal demand flow from here with some passengers using Birmingham Interchange station. The network also provides a poorer service to Yorkshire, which results in lower demand there as well. The journey times to the North East and Scotland are somewhat slower than in the Inverse A so the Reverse S exhibits lower demand from here as well. 121

122 HS2 Demand Model Analysis The Reverse E does not improve the journey experience of travellers between London and the North West over and above what they would get from HS2 to Birmingham. This limits the number of rail trips between London and the North West (in effect the level of demand would be no higher than the HS2 central case had these tests been conducted on a comparable basis which they are not) Any of the three networks would revolutionise the London to Scotland rail market, and bring it into direct competition with the air market. Indeed nearly 50% of additional rail travellers are shifting from air. This represents a reduction in air journeys by around 60% between the regions for all the modelled scenarios. This kind of effect is generally expected for rail journey times getting close to three hours. Benefits The Inverse A provides the biggest benefits and generates the largest additional revenue. This is followed by the Reverse E. The difference reflects better journey times to the North West and Scotland where the Inverse A is the fastest and most comprehensive network. The Reverse S is estimated to bring lower benefits and revenues mainly because it does not serve the East Midlands and South Yorkshire Most of the benefits occur in improved time savings and travel experience on the rail network. Around 6% of the benefits arise through improved travel conditions on the road network as a consequence of mode shift. The following maps illustrate the rail benefits by originating district under the three network configurations. 122

123 Chapter 11: A Long Term Strategy for High Speed Rail Figure Benefits by Trip Origin for the Three Network Configurations Inverse A Reverse E Reverse S 123

124 HS2 Demand Model Analysis The regional results suggest journey times to London are important for the benefits of high speed rail to Scotland. The Reverse E loses more than 30% of Scottish benefits compared to the Inverse A, the Reverse S over 35% The North West is clearly best served by the Inverse A: Preston is not covered by the other networks while Liverpool gets slower journey times to London in the alternatives. While the Reverse S offers better London connections than the Reverse E, the latter provides better cross-country connectivity to the region. This offsets the disadvantage of slower journeys to London to some extent As expected, the North East, Yorkshire and Humber as well as the East Midlands regions receive broadly comparable benefits under the A and the E while the missing leg via the East Midlands severely disadvantages the Reverse S Figure 11.5 also highlights the importance of areas that are not directly served by the high speed networks. For example the improvements to Glasgow and Edinburgh under the Inverse A are sufficiently strong for travellers from all over Scotland to re-route via high speed thereby benefitting from the changes. This effect is less pronounced in the other two configurations. Costs The costs have been estimated based on the rates and assumptions used for HS2. This section provides a brief overview of how we estimated the drivers behind each cost category. The resulting appraisal costs are provided in the summary Table 11.5b. As before, in line with WebTAG 20 guidance we have for appraisal purposes converted the costs into the market price unit of account. We have discounted them to

125 Chapter 11: A Long Term Strategy for High Speed Rail Table 11.5b: Appraisal Costs, billion in 2009 Prices Costs Inverse A Reverse E Reverse S Capital Expenditure Construction 46.5bn 43.6bn 39.4bn Rolling Stock 8.3bn 8.8bn 7.3bn Total 54.7bn 52.4bn 46.7bn Opex & Maintenance Track 3.5bn 2.9bn 2.4bn Stations 0.6bn 0.6bn 0.4bn Train Maintenance 12.3bn 12.0bn 10.9bn Train Operation 17.0bn 16.1bn 14.9bn Total 33.5bn 31.6bn 28.6bn TOTAL COSTS (PVC) 88.3bn 84.0bn 75.4bn These costs are based on a strategic assessment of route and operating requirements and follow closely the treatment of costs for HS2. We have developed broad infrastructure cost assumptions based on basic unit rates derived from our work on HS2 and calculated using assumptions about the composition of certain routes (e.g. the difficulty of the terrain) The rolling stock requirements are approximated following a similar but simplified approach as for HS2. The calculations take maintenance requirements into account. The inverse A requires a total of 330 high speed captive train sets. No classic compatible services are assumed to run in the Inverse A service specification. The Reverse E and S both need a fleet of 245 high speed captive train sets complemented by 59 classic compatible sets for the Reverse E and 26 for the Reverse S For stations, cost assumptions are based on a high level estimation of the likely number of platforms and station staff required for the number of trains and passengers expected at each of the stations. We have assumed that the stations at Manchester and Leeds would involve similar costs to those estimated for Birmingham Fazely Street in HS2. For Liverpool, Glasgow and Edinburgh we use Old Oak Common as a guide while for Newcastle and the interchange stations, Birmingham interchange is the comparator. 125

126 HS2 Demand Model Analysis 11.6 Benefit Cost Ratios of a Wider Network The table below shows all benefits, revenues and costs for the three networks and summarises them in the benefit cost ratio. The values are present values expressed in 2009 prices and discounted over the 60 year appraisal period. Table Appraisal Summary Table for Wider Network 2009 PV billion Inverse A Reverse E Reverse S Transport User Benefits 102.5bn 86.8bn 73.5bn Other Benefits (excl Carbon) 0.6bn 0.4bn 0.4bn Net Transport Benefits 103.1bn 87.3bn 73.9bn Capital Costs 54.7bn 52.4bn 46.7bn Operating Costs 33.5bn 31.6bn 28.2bn Total Costs 88.3bn 84.0bn 75.4bn Revenues 48.4bn 42.1bn 38.1bn Indirect Tax - 4.9bn - 4.4bn - 3.9bn Benefit Cost Ratio The analysis suggests there is a good case for a wider high speed network. The Inverse A performs the most strongly of the three networks considered, despite being the most costly. The wider coverage and faster journey times deliver benefits which more than offset this additional cost The values would no doubt change if further work on engineering options and benefits were carried out. However, at this stage it does not appear likely that any of these changes would affect any one of the networks significantly differently from the others, though the inverse A might offer more options for released capacity on the East Cost Mainline (ECML) and the Midlands Mainline (MML). Overall the conclusion that the Inverse A performs the best of the three networks considered due to its better journey times and wider coverage is considered to be robust. 126

127 Chapter 11: A Long Term Strategy for High Speed Rail 11.7 Limitations of Our Analysis and Further Work The purpose of our work on the wider network was to undertake a strategic assessment of the longer term strategy rather than to optimise the shape and design of such a network. We have shown that out of the three networks tested, the Inverse A performs best in terms of the indicative benefit cost ratio. However, it is reasonable to expect that the business case for the networks could be substantially improved following a more detailed consideration of issues such as: Optimal capacity - As outlined above, we have assumed the maximum capacity that could be provided. While this assumption may provide strong benefits, it also implies higher operating costs and rolling stock requirements. We have not optimised service patterns to demand, or considered in detail the business case for incremental sections of line (other than Manchester and Leeds below). Released capacity Similarly we have not attempted to re-optimise the use of the classic rail network. Reliability On the HS2 route, this contributes around 10% to its business case. A wider network would, if anything, be expected to bring larger improvements to reliability as fewer hybrid services reduce the potential for importing delays from the classic rail network. Wider impacts Wider impacts amount to almost 15% on top of the conventional benefits of HS2. The more extensive networks discussed here might be expected to generate even more significant indirect impacts on the economy From our analysis we can conclude that a wider network could provide good value for money and that the Inverse A provides the best case of the options considered. However this does not mean that the networks we have considered are the optimal solutions. We have not considered, for example a combination of classic line upgrades, hybrid running and some entirely new, high speed links. Whilst this may deliver lower benefits it could be at a much lower costs, thereby offering a better overall business case. More work would be required to fully understand the impact on a business case of these kinds of options Extensions to Manchester and Leeds Having concluded that a network configuration with branches to the east and west of the Pennines performs best of those we tested, we looked at the strategic case for incremental components of this configuration, focussing on the likely next steps building on the base that HS2 provides. 127

128 HS2 Demand Model Analysis Extending HS2 to Manchester would be an obvious and fairly low cost next step. Greater Manchester is the next largest urban conurbation in the UK, and the area is already benefitting from classic compatible trains serving it in the Day One scenario. This would mean an extension to Manchester would have relatively low additional operating costs. An extension to Leeds on the other hand would bring the experience of high speed travel to wholly new areas, potentially unlocking large demand from Leeds, Sheffield and the East Midlands This section summarises the work done on possible extensions to Manchester and Leeds via an eastern alignment. The modelling undertaken for this section is closer to the analysis of HS2 and differs in some key points from the approach used for the wider networks above. These differences are summarised first before the results of the two scenarios are summarised individually. Modelling Approach In contrast to the wider network analysis presented above, we have modelled the extensions to Manchester and Leeds building on from the HS2 Day One scenario. This means that high speed services to Birmingham and Manchester have already replaced the current WCML Pendolino services and some of the released capacity has been re-used in the London and Birmingham areas. We have not, however, made any further changes to the pattern of using the released capacity as derived for the Day One specification An extension to Manchester would most likely include an interchange station similar to that near Birmingham International Airport. While we have made an allowance for such a stop in our journey time assumption to Manchester central, our modelling does not capture this demand and we have not included the likely benefits of it. This results in some disbenefits to areas around Wilmslow and Stockport where the hybrid Manchester bound trains stop on Day One and would potentially use an interchange station if the modelling was able to include this We have followed the same approach on reliability as in Day One and adjusted the assumptions to reflect the likely further improvements to Manchester and Leeds respectively For seat capacity we use the same assumption as for the Day One specification. This means that we have allowed for some 400m trains at certain times of day, running on the dedicated high speed network, but only 200m classic compatible trains. As in the wider networks above, we have not considered any new stations but used existing stations instead. Manchester Extending HS2 from the West Midlands to Manchester is estimated to bring reductions in journey times from London to Manchester of 20 minutes on top of what is already achieved on Day One. London based hybrid services to Scotland, Preston and Liverpool save another 13 minutes over the Day One service specification. The only other change to the Day One specification is the addition of three trains per hour connecting Birmingham to Manchester, taking 54 minutes to complete the journey. 128

129 Chapter 11: A Long Term Strategy for High Speed Rail The precise line of route chosen has a direct impact especially on the hybrid services. The high level analysis undertaken at this stage suggests a route approaching Manchester centre from the east has significant engineering advantages. However, it requires a fairly long line south of the city to reconnect to the WCML. The length of line connecting services to the WCML limits the benefits of the extension to places beyond Manchester If a more westerly alignment of the route could be identified, the journey times to Liverpool, Preston and Scotland would be further improved. Such a design, however, might compromise a later extension through the Pennines towards Leeds. The modelling undertaken here is based on the easterly approach but further testing would be needed if a detailed line of route were developed Table 11.8a shows the daily passenger flows on high speed services between London and the regions. Scotland and the North West are clearly seeing an increase in trips to or from the capital. In total there are forecast to be just under 10% more users compared to Day One. Table 11.8a Daily Passenger Flows between London and the Regions for HS2 Manchester Extension Daily Demand to/from London HS2 Day One Manchester Extension Difference Scotland 11,300 15,100 3,800 North East North West 54,700 58,900 4,200 Yorkshire and Humberside 5,200 6, West Midlands 40,100 40, East Midlands 1,200 1, Total 112, ,800 9, In addition to the increase in demand to and from London, the journey time and capacity improvements between Birmingham and Manchester result in 6,000 trips per day between the West Midlands and the North West on high speed services as well as around 1,400 daily tips between the West Midlands and Yorkshire & Humber. Less than half of these are switching from classic rail The extension benefits: the additional users who would not have travelled in the Day One scenario. These users also generate additional revenue. those who were already using hybrid services from and to London under Day One who are now reaching their destinations faster. Travellers switching from classic to high speed services on the cross country services who now benefit from shorter journey times. 129

130 HS2 Demand Model Analysis Figure 11.8a shows rail benefits by trip origin and how they change between Day One and a Manchester extension. It shows that the areas that benefit from the Manchester extension are the same as those under Day One, but that the benefits are increased. Figure 11.8a - Rail Benefits by Trip Origin for HS2 s Day One Scenario and the Manchester Extension Day One Manchester Extension The incremental benefits and revenues of the Manchester extension over those of Day One are shown in Table 11.8b below together with a summary of the additional costs. The values are shown discounted to 2009 values and prices. 130

131 Chapter 11: A Long Term Strategy for High Speed Rail Table 11.8b Incremental Benefits and Costs for HS2 Extension to Manchester Quantified Costs and Benefits PV 2009 discount year and prices billion Transport User Benefits Other Benefits (excl Carbon) Net Transport Benefits Capital Costs Operating Costs Total Costs Revenues Indirect Tax 8.1bn 0.0bn 8.1bn 4.8bn 2.5bn 7.3bn 4.0bn - 0.4bn Benefit Cost Ratio On the cost side, a substantial part of the operating costs is already included in Day One costs. The classic compatible trains operating between London and Manchester from Day One are actually more expensive to run than single high speed captive train sets. Running 400m trains during peak hours, however, adds to the rolling stock and running costs, more than offsetting that cost saving The additional rolling stock capital expenditure contributes 550m to the present value of costs (PVC). Discounted to 2009 and expressed in market prices, the infrastructure costs for extending the high speed line is estimated to total 4.8bn. Operating costs over 60 years would be expected to add 2.5bn to the PVC which sum to 7.3bn in total Based on the quantified impacts above, the indicative business case for a Manchester extension is good with about 2.20 worth of benefits for every pound of net expenditure. Leeds While an extension to Manchester would essentially bring further improvements to regions already benefitting from hybrid services on Day One, an extension to Leeds would bring the experience of high speed rail travel to the eastern half of the country Fastest journey times to London on this route would be 53 minutes for Nottingham, 1h15 for Sheffield and 1h20 in the case of Leeds. For all these connections, the time savings exceed 50 minutes. Hybrid trains to Newcastle bring a reduction of 15 minutes against the current fastest services. In addition cross country connections between Birmingham and Leeds would fall to 65 minutes and between Birmingham and Newcastle to 2h20 savings of more than 50 minutes in each case. 131

132 HS2 Demand Model Analysis As shown in Table 11.8c below, in terms of high speed trips to or from London, the extension to Leeds adds a significant number of trips to the Eastern regions where we would not expect HS2 to have much impact. In total, an additional 70,000 trips per day would be likely to flow in and out of London. Table 11.8c Daily Passenger flows between London and the regions for HS2 Leeds extensions Daily Demand to/from London HS2 day1 Leeds Extension Difference Scotland 11,300 11,300 0 North East 0 15,400 15,400 North West 54,700 55, Yorkshire and Humberside 5,200 39,400 34,200 West Midlands 40,100 40, East Midlands 1,200 20,400 19,200 Total 112, ,400 69, In terms of cross country flows, the Leeds extension is forecast to carry around 8,000 passengers per day between West and East Midlands and a similar number between the West Midlands and Yorkshire & Humber. Around 60% of these high speed journeys replace trips on the classic network. Between the West Midlands and the North East, 75% of the 3,000 trips per day come from classic rail The high speed extension to Leeds benefits: Existing rail travellers between London and the eastern regions through improved services. A significant number of cross country rail users that experience similar improvements. Additional rail users who would have either used other modes or not travelled under Day One Figure 11.8b below highlight the focus of benefits on rail users in regions not significantly benefiting from the line to the West Midlands. The large majority of districts that benefit are located towards the east of those benefitting on Day One. In addition, the benefits to cross country travellers starting their journeys in the West Midlands are clearly visible. 132

133 Chapter 11: A Long Term Strategy for High Speed Rail Figure 11.8b - Rail Benefits by Trip Origin for HS2 Day One Scenario and the Leeds Extension Day One Leeds Extension Table 11.8d summarises the benefits, revenues and costs that are estimated additional to those for the route to the West Midlands. Table 11.8d Incremental Benefits and Costs for HS2 extension to Leeds Quantified Costs and Benefits PV 2009 discount year and prices billion Transport User Benefits Other Benefits (excl Carbon) Net Transport Benefits Capital Costs Operating Costs Total Costs Revenues Indirect Tax 30.4bn - 0.1bn 30.3bn 6.4bn 7.3bn 13.6bn 13.9bn - 1.5bn Benefit Cost Ratio

134 HS2 Demand Model Analysis While the new route is longer, it is expected to be comparatively cheaper to construct due to the likely easier topography around potential line of route. In total we estimate the cost of construction to be similar to that of the Manchester extension. However, the additional rolling stock would be entirely additional to the Day One scenario, adding substantially to capital expenditure The substantial additional number of trips is also expected to generate significant revenue flows. Indeed, based on this illustrative modelling, the revenues come close to paying for the costs of the extension over a 60 years appraisal period resulting in a high benefit cost ratio The overall magnitude of benefits compared to the costs suggests a strong business case for the Leeds extension. 134

135 Appendix 1: Transport Economic Efficiency Tables

136 HS2 Demand Model Analysis A1.1 Introduction A1.1.1 This appendix provides the Transport Economic Efficiency (TEE) tables for tests undertaken using the final version of our demand model. These are the Central case (Day One scenario) Classic line alternative Central case without reliability Central case without a station at Old Oak Common Central case without a Birmingham Interchange station Central case with a station at Heathrow Wider Networks The Inverse A Wider Networks The Reverse E Wider Networks The Reverse S HS2 Extensions Manchester HS2 Extensions Leeds A1.1.2 A1.1.3 The TEE tables compare each of these scenarios against the do minimum reference case, essentially a world without high speed rail. All data are presented in present values and 2009 prices. It should be noted that the Day One results have been subject to a final minor amendment that has not been applied to the other tests yet. As a result the benefits set out in Figure A1.1 are not directly comparable with the other TEE tables. Where appropriate, consistent comparisons have been set out in Chapter 11 (Leeds and Manchester extensions) and Appendix 2 (sensitivity tests). 136

137 Appendix 1: Transport Economic Efficiency Tables Figure A1.1 Day One Central Case (Chapter 10) TEE/Public Accounts Table All Outputs Day One Table 1: Economic Efficiency of Transport System ( mill, revenues are scored as positives, costs as negatives) Total Other Rail Consumers user benefits - travel time saving 10, ,833 - Vehicle opcost user charges during construction & maintenance Net (1) 10, ,833 Business User benefits - Travel time 17,404 1,279 16,125 - Vehicle opcost user charges during construction & maintenance Net (2) 17,390 1,326 16,125 Private sector provider impact - revenue 15,003-15,003 - opcost - 7, ,602 - investment cost - 17, ,850 - grant/subsidy 25,452-25,452 - revenue transfer - 15, ,003 Sub total (3) Other impacts - Developer contribution (4) - - Net business impact (5 = 2+3+4) 17,390 1,326 16,125 Total, PV of transport econ eff. Benefits (6 = 1+5) 27,896 Table 2 Public Accounts ( mill costs should be recorded as a positive number, surpluses as a negative one) All Modes Other Rail Total Local Government funding - Direct Revenue Op costs - - Investment costs - - Developer and other contributions - - Grant/Subsidy (k)* - - Revenue transfer - Net (7) Central Government funding - Direct Revenue Op costs - - Investment costs* - - Developer and other contributions - - Grant/Subsidy (k)* 25,452 25,452 - Indirect Tax Revenues (i) 1, ,433 - Revenue transfer - 15, ,003 Net (8) 11, ,881 Total PV of costs (9 =7+8) 11,913 Table 3: Analysis of Monetised Costs and Benefits (AMCB) Total Noise 3 Local air quality 5 Journey Greenhous ambience gases g y, crowding) 768 Accidents (incl. safety) 36 Consumer users (sub-total 1, Table 1) 10,506 Business users and providers (sub-total 5, Table 1) 17,390 Reliability (incl. performance & reliability) - Option values - Interchange (station quality and crowding) - PVB (a = sum of all benefits) 28,708 PVC (b = sub-total 9, Table 2) 11,913 Overall impact, total - NPV (a-b) 16,794 - BCR (a/b) Revised BCR (a-i)/(b-i)

138 HS2 Demand Model Analysis Figure A1.2 - Classic Line Alternative (Appendix 2, Section 5) TEE/Public Accounts Table All Outputs Classic Line Alternative Table 1: Economic Efficiency of Transport System ( mill, revenues are scored as positives, costs as negatives) Total Other Rail Consumers user benefits - travel time saving 6, ,140 - Vehicle opcost user charges during construction & maintenance Net (1) 6, ,140 Business User benefits - Travel time 15, ,012 - Vehicle opcost user charges during construction & maintenance Net (2) 14, ,012 Private sector provider impact - revenue 12,131-12,131 - opcost - 7, ,068 - investment cost - 15, ,250 - grant/subsidy 22,318-22,318 - revenue transfer - 12, ,131 Sub total (3) Other impacts - Developer contribution (4) - - Net business impact (5 = 2+3+4) 14, ,012 Total, PV of transport econ eff. Benefits (6 = 1+5) 21,691 Table 2 Public Accounts ( mill costs should be recorded as a positive number, surpluses as a negative one) All Modes Other Rail Total Local Government funding - Direct Revenue Op costs - - Investment costs - - Developer and other contributions - - Grant/Subsidy (k)* - - Revenue transfer - Net (7) Central Government funding - Direct Revenue Op costs - - Investment costs* - - Developer and other contributions - - Grant/Subsidy (k)* 22,318 22,318 - Indirect Tax Revenues (i) 1, ,282 - Revenue transfer - 12,131-12,131 Net (8) 11, ,469 Total PV of costs (9 =7+8) 11,502 Table 3: Analysis of Monetised Costs and Benefits (AMCB) Total Noise 3 Local air quality 5 Journey Greenhous ambience gases g y, crowding) 735 Accidents (incl. safety) 37 Consumer users (sub-total 1, Table 1) 6,706 Business users and providers (sub-total 5, Table 1) 14,985 Reliability (incl. performance & reliability) - Option values - Interchange (station quality and crowding) - PVB (a = sum of all benefits) 22,471 PVC (b = sub-total 9, Table 2) 11,502 Overall impact, total - NPV (a-b) 10,969 - BCR (a/b) Revised BCR (a-i)/(b-i)

139 Appendix 1: Transport Economic Efficiency Tables Figure A1.3 - Central Scenario without Reliability Adjustment (Section 3.4) TEE/Public Accounts Table All Outputs No Reliability Table 1: Economic Efficiency of Transport System ( mill, revenues are scored as positives, costs as negatives) Total Other Rail Consumers user benefits - travel time saving 7, ,108 - Vehicle opcost user charges during construction & maintenance Net (1) 7, ,108 Business User benefits - Travel time 18,148 1,173 16,975 - Vehicle opcost user charges during construction & maintenance Net (2) 18,134 1,159 16,975 Private sector provider impact - revenue 14,056-14,056 - opcost - 7, ,602 - investment cost - 17, ,850 - grant/subsidy 25,452-25,452 - revenue transfer - 14, ,056 Sub total (3) Other impacts - Developer contribution (4) - - Net business impact (5 = 2+3+4) 18,134 1,159 16,975 Total, PV of transport econ eff. Benefits (6 = 1+5) 25,892 Table 2 Public Accounts ( mill costs should be recorded as a positive number, surpluses as a negative one) All Modes Other Rail Total Local Government funding - Direct Revenue Op costs - - Investment costs - - Developer and other contributions - - Grant/Subsidy (k)* - - Revenue transfer - Net (7) Central Government funding - Direct Revenue Op costs - - Investment costs* - - Developer and other contributions - - Grant/Subsidy (k)* 25,452 25,452 - Indirect Tax Revenues (i) 1, ,461 - Revenue transfer - 14,056-14,056 Net (8) 12, ,857 Total PV of costs (9 =7+8) 12,891 Table 3: Analysis of Monetised Costs and Benefits (AMCB) Total Noise 3 Local air quality 6 Journey Greenhous ambience gases g y, crowding) 767 Accidents (incl. safety) 39 Consumer users (sub-total 1, Table 1) 7,759 Business users and providers (sub-total 5, Table 1) 18,134 Reliability (incl. performance & reliability) - Option values - Interchange (station quality and crowding) - PVB (a = sum of all benefits) 26,708 PVC (b = sub-total 9, Table 2) 12,891 Overall impact, total - NPV (a-b) 13,816 - BCR (a/b) Revised BCR (a-i)/(b-i)

140 HS2 Demand Model Analysis Figure A1.4 - Central Scenario without Old Oak Station (Chapter 5) TEE/Public Accounts Table All Outputs No Old Oak Station Table 1: Economic Efficiency of Transport System ( mill, revenues are scored as positives, costs as negatives) Total Other Rail Consumers user benefits - travel time saving 7, ,274 - Vehicle opcost user charges during construction & maintenance Net (1) 7, ,274 Business User benefits - Travel time 18,434 1,184 17,249 - Vehicle opcost user charges during construction & maintenance Net (2) 18,419 1,169 17,249 Private sector provider impact - revenue 13,468-13,468 - opcost - 7, ,502 - investment cost - 17, ,194 - grant/subsidy 24,696-24,696 - revenue transfer - 13, ,468 Sub total (3) Other impacts - Developer contribution (4) - - Net business impact (5 = 2+3+4) 18,419 1,169 17,249 Total, PV of transport econ eff. Benefits (6 = 1+5) 26,351 Table 2 Public Accounts ( mill costs should be recorded as a positive number, surpluses as a negative one) All Modes Highway/Air Rail Total Local Government funding - Direct Revenue Op costs - - Investment costs - - Developer and other contributions - - Grant/Subsidy (k)* - - Revenue transfer - Net (7) Central Government funding - Direct Revenue Op costs - - Investment costs* - - Developer and other contributions - - Grant/Subsidy (k)* 24,696 24,696 - Indirect Tax Revenues (i) 1, ,407 - Revenue transfer - 13,468-13,468 Net (8) 12, ,635 Total PV of costs (9 =7+8) 12,672 Table 3: Analysis of Monetised Costs and Benefits (AMCB) Total Noise 3 Local air quality 6 Journey Greenhous ambience gases g y, crowding) 958 Accidents (incl. safety) 41 Consumer users (sub-total 1, Table 1) 7,932 Business users and providers (sub-total 5, Table 1) 18,419 Reliability (incl. performance & reliability) - Option values - Interchange (station quality and crowding) - PVB (a = sum of all benefits) 27,358 PVC (b = sub-total 9, Table 2) 12,672 Overall impact, total - NPV (a-b) 14,687 - BCR (a/b) Revised BCR (a-i)/(b-i)

141 Appendix 1: Transport Economic Efficiency Tables Figure A1.5 - Central Scenario without Birmingham Interchange Station (Chapter 8) TEE/Public Accounts Table All Outputs No Birmingham Interchange Table 1: Economic Efficiency of Transport System ( mill, revenues are scored as positives, costs as negatives) Total Other Rail Consumers user benefits - travel time saving 7, ,411 - Vehicle opcost user charges during construction & maintenance Net (1) 8, ,411 Business User benefits - Travel time 19,326 1,191 18,135 - Vehicle opcost user charges during construction & maintenance Net (2) 19,311 1,176 18,135 Private sector provider impact - revenue 14,726-14,726 - opcost - 7, ,526 - investment cost - 17, ,315 - grant/subsidy 24,841-24,841 - revenue transfer - 14, ,726 Sub total (3) Other impacts - Developer contribution (4) - - Net business impact (5 = 2+3+4) 19,311 1,176 18,135 Total, PV of transport econ eff. Benefits (6 = 1+5) 27,378 Table 2 Public Accounts ( mill costs should be recorded as a positive number, surpluses as a negative one) All Modes Other Rail Total Local Government funding - Direct Revenue Op costs - - Investment costs - - Developer and other contributions - - Grant/Subsidy (k)* - - Revenue transfer - Net (7) Central Government funding - Direct Revenue Op costs - - Investment costs* - - Developer and other contributions - - Grant/Subsidy (k)* 24,841 24,841 - Indirect Tax Revenues (i) 1, ,526 - Revenue transfer - 14,726-14,726 Net (8) 11, ,640 Total PV of costs (9 =7+8) 11,673 Table 3: Analysis of Monetised Costs and Benefits (AMCB) Total Noise 3 Local air quality 5 Journey Greenhous ambience gases g y, crowding) 770 Accidents (incl. safety) 37 Consumer users (sub-total 1, Table 1) 8,067 Business users and providers (sub-total 5, Table 1) 19,311 Reliability (incl. performance & reliability) - Option values - Interchange (station quality and crowding) - PVB (a = sum of all benefits) 28,193 PVC (b = sub-total 9, Table 2) 11,673 Overall impact, total - NPV (a-b) 16,519 - BCR (a/b) Revised BCR (a-i)/(b-i)

142 HS2 Demand Model Analysis Figure A1.6 - Central Scenario with a Heathrow Through Station (Chapter 5). (Costs based on a Station at Iver) TEE/Public Accounts Table All Outputs With Heathrow Station Table 1: Economic Efficiency of Transport System ( mill, revenues are scored as positives, costs as negatives) Total Other Rail Consumers user benefits - travel time saving 7, ,965 - Vehicle opcost user charges during construction & maintenance Net (1) 7, ,965 Business User benefits - Travel time 18,152 1,343 16,809 - Vehicle opcost user charges during construction & maintenance Net (2) 18,139 1,330 16,809 Private sector provider impact - revenue 13,731-13,731 - opcost - 7, ,702 - investment cost - 20, ,401 - grant/subsidy 28,103-28,103 - revenue transfer - 13, ,731 Sub total (3) Other impacts - Developer contribution (4) - - Net business impact (5 = 2+3+4) 18,139 1,330 16,809 Total, PV of transport econ eff. Benefits (6 = 1+5) 25,794 Table 2 Public Accounts ( mill costs should be recorded as a positive number, surpluses as a negative one) All Modes Other Rail Total Local Government funding - Direct Revenue Op costs - - Investment costs - - Developer and other contributions - - Grant/Subsidy (k)* - - Revenue transfer - Net (7) Central Government funding - Direct Revenue Op costs - - Investment costs* - - Developer and other contributions - - Grant/Subsidy (k)* 28,103 28,103 - Indirect Tax Revenues (i) 1, ,417 - Revenue transfer - 13,731-13,731 Net (8) 15, ,789 Total PV of costs (9 =7+8) 15,819 Table 3: Analysis of Monetised Costs and Benefits (AMCB) Total Noise 3 Local air quality 5 Journey Greenhouse ambience gases(incl. rolling stock quality, and in vehicle crowding) 832 Accidents (incl. safety) 34 Consumer users (sub-total 1, Table 1) 7,655 Business users and providers (sub-total 5, Table 1) 18,139 Reliability (incl. performance & reliability) - Option values - Interchange (station quality and crowding) - PVB (a = sum of all benefits) 26,668 PVC (b = sub-total 9, Table 2) 15,819 Overall impact, total - NPV (a-b) 10,849 - BCR (a/b) Revised BCR (a-i)/(b-i)

143 Appendix 1: Transport Economic Efficiency Tables Figure A1.7 - Wider Network Tests The Inverse A (Chapter 11) TEE/Public Accounts Table All Outputs Inverse A Table 1: Economic Efficiency of Transport System ( mill, revenues are scored as positives, costs as negatives) Total Other Rail Consumers user benefits - travel time saving 26,369 1,433 24,936 - Vehicle opcost user charges during construction & maintenance Net (1) 27,161 2,225 24,936 Business User benefits - Travel time 75,307 4,238 71,069 - Vehicle opcost user charges during construction & maintenance Net (2) 75,335 4,266 71,069 Private sector provider impact - revenue 48,361-48,361 - opcost - 33, ,548 - investment cost - 54, ,732 - grant/subsidy 88,281-88,281 - revenue transfer - 48, ,361 Sub total (3) Other impacts - Developer contribution (4) - - Net business impact (5 = 2+3+4) 75,335 4,266 71,069 Total, PV of transport econ eff. Benefits (6 = 1+5) 102,496 Table 2 Public Accounts ( mill costs should be recorded as a positive number, surpluses as a negative one) All Modes Other Rail Total Local Government funding - Direct Revenue Op costs - - Investment costs - - Developer and other contributions - - Grant/Subsidy (k)* - - Revenue transfer - Net (7) Central Government funding - Direct Revenue Op costs - - Investment costs* - - Developer and other contributions - - Grant/Subsidy (k)* 88,281 88,281 - Indirect Tax Revenues (i) 4, ,862 - Revenue transfer - 48,361-48,361 Net (8) 44, ,782 Total PV of costs (9 =7+8) 44,848 Table 3: Analysis of Monetised Costs and Benefits (AMCB) Total Noise 6 Local air quality 11 Journey Greenhous ambience gases g y, crowding) 509 Accidents (incl. safety) 76 Consumer users (sub-total 1, Table 1) 27,161 Business users and providers (sub-total 5, Table 1) 75,335 Reliability (incl. performance & reliability) - Option values - Interchange (station quality and crowding) - PVB (a = sum of all benefits) 103,097 PVC (b = sub-total 9, Table 2) 44,848 Overall impact, total - NPV (a-b) 58,250 - BCR (a/b) Revised BCR (a-i)/(b-i)

144 HS2 Demand Model Analysis Figure A1.8 - Wider Network Tests The Reverse E (Chapter 11) TEE/Public Accounts Table All Outputs Reverse E Table 1: Economic Efficiency of Transport System ( mill, revenues are scored as positives, costs as negatives) Total Other Rail Consumers user benefits - travel time saving 23,721 1,262 22,459 - Vehicle opcost user charges during construction & maintenance Net (1) 24,438 1,979 22,459 Business User benefits - Travel time 63,538 3,783 59,755 - Vehicle opcost user charges during construction & maintenance Net (2) 63,559 3,804 59,755 Private sector provider impact - revenue 42,123-42,123 - opcost - 31, ,638 - investment cost - 52, ,377 - grant/subsidy 84,015-84,015 - revenue transfer - 42, ,123 Sub total (3) Other impacts - Developer contribution (4) - - Net business impact (5 = 2+3+4) 63,559 3,804 59,755 Total, PV of transport econ eff. Benefits (6 = 1+5) 87,996 Table 2 Public Accounts ( mill costs should be recorded as a positive number, surpluses as a negative one) All Modes Other Rail Total Local Government funding - Direct Revenue Op costs - - Investment costs - - Developer and other contributions - - Grant/Subsidy (k)* - - Revenue transfer - Net (7) Central Government funding - Direct Revenue Op costs - - Investment costs* - - Developer and other contributions - - Grant/Subsidy (k)* 84,015 84,015 - Indirect Tax Revenues (i) 4, ,302 - Revenue transfer - 42,123-42,123 Net (8) 46, ,194 Total PV of costs (9 =7+8) 46,248 Table 3: Analysis of Monetised Costs and Benefits (AMCB) Total Noise 5 Local air quality 9 Journey Greenhous ambience gases g y, crowding) 369 Accidents (incl. safety) 63 Consumer users (sub-total 1, Table 1) 24,438 Business users and providers (sub-total 5, Table 1) 63,559 Reliability (incl. performance & reliability) - Option values - Interchange (station quality and crowding) - PVB (a = sum of all benefits) 88,442 PVC (b = sub-total 9, Table 2) 46,248 Overall impact, total - NPV (a-b) 42,194 - BCR (a/b) Revised BCR (a-i)/(b-i)

145 Appendix 1: Transport Economic Efficiency Tables Figure A1.9 - Wider Network Tests The Reverse S (Chapter 11) TEE/Public Accounts Table All Outputs Reverse S Table 1: Economic Efficiency of Transport System ( mill, revenues are scored as positives, costs as negatives) Total Other Rail Consumers user benefits - travel time saving 19,608 1,007 18,601 - Vehicle opcost user charges during construction & maintenance Net (1) 20,152 1,551 18,601 Business User benefits - Travel time 53,357 2,988 50,369 - Vehicle opcost user charges during construction & maintenance Net (2) 53,369 3,000 50,369 Private sector provider impact - revenue 38,113-38,113 - opcost - 28, ,631 - investment cost - 46, ,728 - grant/subsidy 75,359-75,359 - revenue transfer - 38, ,113 Sub total (3) Other impacts - Developer contribution (4) - - Net business impact (5 = 2+3+4) 53,369 3,000 50,369 Total, PV of transport econ eff. Benefits (6 = 1+5) 73,521 Table 2 Public Accounts ( mill costs should be recorded as a positive number, surpluses as a negative one) All Modes Other Rail Total Local Government funding - Direct Revenue Op costs - - Investment costs - - Developer and other contributions - - Grant/Subsidy (k)* - - Revenue transfer - Net (7) Central Government funding - Direct Revenue Op costs - - Investment costs* - - Developer and other contributions - - Grant/Subsidy (k)* 75,359 75,359 - Indirect Tax Revenues (i) 3, ,877 - Revenue transfer - 38,113-38,113 Net (8) 41, ,123 Total PV of costs (9 =7+8) 41,166 Table 3: Analysis of Monetised Costs and Benefits (AMCB) Total Noise 4 Local air quality 7 Journey Greenhous ambience gases g y, crowding) 304 Accidents (incl. safety) 50 Consumer users (sub-total 1, Table 1) 20,152 Business users and providers (sub-total 5, Table 1) 53,369 Reliability (incl. performance & reliability) - Option values - Interchange (station quality and crowding) - PVB (a = sum of all benefits) 73,886 PVC (b = sub-total 9, Table 2) 41,166 Overall impact, total - NPV (a-b) 32,720 - BCR (a/b) Revised BCR (a-i)/(b-i)

146 HS2 Demand Model Analysis Figure A HS2 Extension to Manchester (Chapter 11) TEE/Public Accounts Table All Outputs Manchester Extension Table 1: Economic Efficiency of Transport System ( mill, revenues are scored as positives, costs as negatives) Total Other Rail Consumers user benefits - travel time saving 10, ,447 - Vehicle opcost user charges during construction & maintenance Net (1) 10, ,447 Business User benefits - Travel time 26,193 1,718 24,475 - Vehicle opcost user charges during construction & maintenance Net (2) 26,184 1,709 24,475 - Private sector provider impact - revenue 19,055-19,055 - opcost - 10, ,103 - investment cost - 22, ,653 - grant/subsidy 32,756-32,756 - revenue transfer - 19, ,055 Sub total (3) Other impacts - Developer contribution (4) - - Net business impact (5 = 2+3+4) 26,184 1,709 24,475 Total, PV of transport econ eff. Benefits (6 = 1+5) 36,493 Table 2 Public Accounts ( mill costs should be recorded as a positive number, surpluses as a negative one) All Modes Other Rail Total Local Government funding - Direct Revenue Op costs - - Investment costs - - Developer and other contributions - - Grant/Subsidy (k)* - - Revenue transfer - Net (7) Central Government funding - Direct Revenue Op costs - - Investment costs* - - Developer and other contributions - - Grant/Subsidy (k)* 32,756 32,756 - Indirect Tax Revenues (i) 1, ,935 - Revenue transfer - 19,055-19,055 Net (8) 15, ,637 Total PV of costs (9 =7+8) 15,672 Table 3: Analysis of Monetised Costs and Benefits (AMCB) Total Noise 3 Local air quality 6 Journey Greenhous ambience gases crowding) 750 Accidents (incl. safety) 40 Consumer users (sub-total 1, Table 1) 10,309 Business users and providers (sub-total 5, Table 1) 26,184 Reliability (incl. performance & reliability) - Option values - Interchange (station quality and crowding) - PVB (a = sum of all benefits) 37,292 PVC (b = sub-total 9, Table 2) 15,672 Overall impact, total - NPV (a-b) 21,620 - BCR (a/b) Revised BCR (a-i)/(b-i)

147 Appendix 1: Transport Economic Efficiency Tables Figure A HS2 Extension to Leeds (Chapter 11) TEE/Public Accounts Table All Outputs Leeds Extension Table 1: Economic Efficiency of Transport System ( mill, revenues are scored as positives, costs as negatives) Total Other Rail Consumers user benefits - travel time saving 16, ,867 - Vehicle opcost user charges during construction & maintenance Net (1) 17,271 1,403 15,867 Business User benefits - Travel time 41,690 2,803 38,887 - Vehicle opcost user charges during construction & maintenance Net (2) 41,698 2,811 38,887 Private sector provider impact - revenue 28,937-28,937 - opcost - 14, ,857 - investment cost - 24, ,215 - grant/subsidy 39,072-39,072 - revenue transfer - 28, ,937 Sub total (3) Other impacts - Developer contribution (4) - - Net business impact (5 = 2+3+4) 41,698 2,811 38,887 Total, PV of transport econ eff. Benefits (6 = 1+5) 58,969 Table 2 Public Accounts ( mill costs should be recorded as a positive number, surpluses as a negative one) All Modes Other Rail Total Local Government funding - Direct Revenue Op costs - - Investment costs - - Developer and other contributions - - Grant/Subsidy (k)* - - Revenue transfer - Net (7) Central Government funding - Direct Revenue Op costs - - Investment costs* - - Developer and other contributions - - Grant/Subsidy (k)* 39,072 39,072 - Indirect Tax Revenues (i) 3, ,024 - Revenue transfer - 28,937-28,937 Net (8) 13, ,159 Total PV of costs (9 =7+8) 13,206 Table 3: Analysis of Monetised Costs and Benefits (AMCB) Total Noise 4 Local air quality 7 Journey Greenhous ambience gases(incl. rolling stock quality, and in vehicle crowding) 863 Accidents (incl. safety) 52 Consumer users (sub-total 1, Table 1) 17,271 Business users and providers (sub-total 5, Table 1) 41,698 Reliability (incl. performance & reliability) - Option values - Interchange (station quality and crowding) - PVB (a = sum of all benefits) 59,896 PVC (b = sub-total 9, Table 2) 13,206 Overall impact, total - NPV (a-b) 46,690 - BCR (a/b) Revised BCR (a-i)/(b-i)

148 Appendix 2: Sensitivity Tests on HS2 Central Case

149 Appendix 2: Transport Economic Efficiency Tables A2.1 Testing Our Assumptions A2.1.1 A2.1.2 Analysis demonstrates that, under our central assumptions, HS2 would deliver strong benefits and a good overall business case. As far as possible we have sought to base our central case on conservative assumptions. This appendix reports the results of some of the critical sensitivity tests we have undertaken. The results presented here use the final version of the model that has been developed for us. However since finalising the model runs there has been a minor correction made to the estimation of benefits specifically the weightings applied to crowding and other elements of generalised journey time. This has resulted in small changes in the overall benefits of the scheme, but should not affect the pattern of benefits across different tests. The results presented in Chapter 10 have been updated to reflect these changes. However we have not yet updated the sensitivity tests outlined below. This should not change the relative comparison between model runs. A2.2 Changing the forecast level of demand for long distance rail trips A2.2.1 A2.2.2 Chapter 3 outlines the assumptions we have used about growth in transport demand without HS2. These assumptions are based on standard forecasting approaches used in the rail industry (in particular the Passenger Demand Forecasting Handbook). However we also highlight the uncertainties and limitations in these approaches. Our model considers the impact of HS2 in two modelled years 2021 and We can view these as the impact of HS2 given two different levels of underlying demand (D1 and D2). The model then estimates the annual benefits of HS2 at each of these two levels of demand. For the purposes of appraisal we need to calculate the Present Value of benefits by discounting over 60 years. To do this we need a time profile of benefits, which is calculated through extrapolation. Essentially this is shown by the blue line in figure A2.1. This assumes: The level of benefits associated with the level of demand D1 (the pink dotted line) is achieved at The Level of benefits associated with the level of demand D2 (the yellow dotted line) is achieved at The level of demand in years between 2021 and 2033 are calculated using linear extrapolation between these two points. The level of benefits in years after 2033 is capped at the 2033 level Whilst the benefits in terms of time savings, crowding etc are held fixed, the values applied to these are assumed to grow in line with WebTAG guidance. Hence there is some growth in benefits beyond However this a function of the appraisal guidance and not changes in modelled output. 149

150 HS2 Demand Model Analysis Figure A2.1 - Illustration of Extrapolation In Sensitivity Tests Annual Benefits D1 Year Central case Half Growth Rate D2 Cap at 2026 A2.2.3 We can easily adjust these assumptions. For example, if demand growth were slower, then this would mean the benefits associated with the level of demand D1 would still occur, it is just that they would arrive a few years later. This is illustrated by the purple line in figure A2.1. The benefits associated with the level of demand D1 would still be reached, but this would be at 2036 instead of And the benefits associated with D2 would not be reached until We can extrapolate between these points to estimate the impact of slower growth on the PVB of HS2. A2.2.4 By using this technique we can approximate any growth rate, and any level of cap up to 2033 without the need for large numbers of model runs which were not possible in the time available. The linearity of the extrapolation means this is only an indicative estimate (since there are several nonlinearities such as crowding factors), but it provides some idea of how sensitive the results are to the assumptions. 150

151 Appendix 2: Transport Economic Efficiency Tables Figure A2.2 - Sensitivity Test with Fixed Demand Cap and Lower Growth Rates 3 Sensitivity Test with Fixed Demand Cap and Lower Growth Rates BCR % 10% 20% 30% 40% 50% 60% 70% 80% 90% Reduction in growth rate A2.2.5 A2.2.6 A2.2.7 Figure A2.2 shows how sensitive the business case is to the assumptions on the growth in background demand for rail travel. It assumes that background demand will still reach the level we currently forecast for 2033, but assumes this will be achieved at a later date (i.e. slower growth). If growth were just 25% slower than currently projected (i.e. 2.7% per annum instead of 3.6% per annum), the BCR for scheme opening at the end of 2025 (excluding wider economic impacts) would drop below 1.5. As long as background demand growth continues, a lower rate of growth would raise questions about when rather than if the scheme would be value for money. It might suggest the scheme should open later than 2025, but there would still be a good business case at some point in the future. What is more significant is whether there will ever be sufficient demand to justify HS2. Our central case assumes demand will not grow beyond 2033, but we have looked at what would happen if market saturation occurred at a lower level of demand. We have investigated this by applying the cap at earlier rates. 151

152 HS2 Demand Model Analysis Figure A2.3: Sensitivity Test with Fixed Growth Rate and Lower Demand Cap 3 Sensitivity Test with Fixed Growth Rate and Lower Demand Cap BCR Year of Cap A2.2.8 A2.2.9 Figure A2.3 shows what the BCR would be if growth in background demand were capped at various years up to It shows that to achieve a BCR above 1.5, background growth in demand must continue at current rates until at least This represents an increase of at least double today s levels. Both of these sensitivity tests demonstrate that the business case will be dependent on realising the level of demand growth forecast in our central case. Overall a 10% reduction in demand on HS2 would reduce the BCR (excluding wider economic impacts) to 2 and a reduction of just over 20% would reduce it to below

153 Appendix 2: Transport Economic Efficiency Tables A2.3 Changing Background Demand Growth and Prices on Non-Rail Modes A2.3.1 A2.3.2 A2.3.3 A2.3.4 We have not been able to conduct specific model tests of different demand growth or pricing assumptions on non-rail modes. However the business case is likely to be less sensitive to changes in the assumptions on other modes. Overall mode shift accounts for a relatively small proportion of the passengers on HS2, and therefore a relatively small proportion of the benefits. If demand growth for car and air travel were lower, then this would tend to reduce the potential market from which HS2 could draw. It would reduce the number of passengers on HS2. However the impact is likely to be small due to the composition of demand on HS2. Thus since 6% of HS2 passengers come from road, a 10% reduction in road demand could be expected to result in 0.6% reduction in demand on HS2. A similar figure would be true for air demand. Changing prices will have more complex interactions, but may not change the overall market that HS2 can draw from. A passenger who chooses to switch to HS2 without road pricing would most likely continue to use HS2 in the presence of road pricing. Indeed the higher price of car travel is likely to increase the number of passengers on HS2. Again this is likely to be a relatively marginal effect. For example a 10% increase in the price of fuel would correspond to around a 3% fall in traffic, with a corresponding increase of less than 1% in the level of demand on HS2. A third runway at Heathrow is included in our central case. If this were not constructed, there might be additional demand for long distance rail trips as pricing and capacity constraints reduce the number of domestic air trips. DfT forecasts suggest that without a third runway, air demand would fall by just under 7%. If domestic air demand saw the same reduction, and assuming all of these trips transferred to HS2, this would increase HS2 demand by less than 5%. 153

154 HS2 Demand Model Analysis A2.4 Premium Fares A2.4.1 A2.4.2 We modelled our central case on the basis of the same fares for high speed rail and classic rail users. We have also considered the scope for using premium fares on high speed services. The impacts of premium fares are many and complex. It is not the case that a simple percentage premium is applicable across all routes. Instead there would need to be careful management of revenue strategies similar to those already seen on long distance services to maximise use of capacity. The HS2 Model Development Report (Atkins, 2009) provides a summary of the tests undertaken. It shows a summary of the revenue impacts of different levels of premium fares for London- Birmingham and London-Manchester routes (See Figure A2.4). Figure A2.4 Impact of premium fares of revenues for specific routes Business: London-Manchester Business: London-Birmingham 50,000 40,000 30,000 20,000 10, ,000 12,000 10,000 8,000 6,000 4,000 2, % 7% 14% 21% 0% 10% 20% 30% Leisure: London-Manchester Leisure: London-Birmingham 30,000 25,000 20,000 15,000 10,000 5, ,000 12,000 10,000 8,000 6,000 4,000 2, % 7% 14% 21% 0% 10% 20% 30% Source: Atkins (2009). 154

155 Appendix 2: Transport Economic Efficiency Tables A2.4.3 A2.4.4 A2.4.5 The percentage fare premium varies according to the route and journey purpose since it was clear a fixed percentage increase on all routes lead to fares that were too high on very long distance routes. Figure A2.4 shows the change in revenues on different routes and journey purposes as a result of different levels of premium fare. Business generally is less price elastic, and so this leads to a tendency for fare premiums to increase revenues. However even here, the potential may be for only relatively small premiums. For example Manchester business flows (see top left chart in figure A2.4) show a relatively small increase in revenues up to a 7% fare premium. Beyond this, revenues fall as fares increase further. It is not possible at this stage of development to hypothesise the detailed nature of such a strategy. More work is needed in this area. However our preliminary conclusions are: The scope for premium fares is more pronounced in the business market than the more price sensitive leisure market. Small increases in fares may lead to a reduction in revenue, but larger increases may increase net revenue. This is because the first passengers priced off will tend to be new traffic generated by high speed rail (who drive new revenues). At higher fare levels passengers tend to switch to classic rail and so some rail fare revenue is maintained. Competition is key. The availability of non-premium service alternatives would make a big difference to the scope to generate additional revenues through premium fares. Pricing may be an effective tool to manage crowding problems. The demand model suggests there is strong demand and some crowding on certain routes particularly those to Scotland. In the absence of a wider network (where more capacity could be provided), premium fares may offer a tool to manage the crowding levels on these services. A2.4.6 All these conclusions point to the need for more detailed modelling of fares strategies, considering the different potential markets service patterns and peak/off-peak pricing potential. 155

156 HS2 Demand Model Analysis A2.5 Comparison with a classic line A2.5.1 A2.5.2 A2.5.3 A2.5.4 We also examined, as an alternative, the case for a new line running at conventional speed. Our appraisal of a classic line was high level and based on analytical constructs; we applied generalised cost and journey time assumptions to our preferred line of route. If Government wished to proceed with a conventional speed line instead of a high speed line, much more work would be required on route options and design, including consideration of intermediate stations. A new classic line would generate some cost savings over our central case, with some savings on construction and other capital costs. We concluded that the cost of constructing the scheme to conventional speed only might save about 9% of the costs of the high speed line. Given the cost of the classic compatible trains would be much higher than conventional speed trains, a further cost saving would be expected. We assumed that operating and maintenance costs would be comparable. An overall cost saving of the order of 3bn would therefore be possible with a classic line. However this cost saving would only be achieved with a significant time penalty for HS2 passengers. Travelling from London to Birmingham, following the same service pattern as the high speed preferred package, would take an extra 15 minutes, based on standard maximum speeds on the UK network and the acceleration performance of a standard reference train. This would halve the time saving from a high speed train. This would reduce the number of people travelling on the line by 20% causing overall benefits to fall by 23% or 6.7bn (see Table A2.5). Revenues would fall by around 19%, or 2.9bn, which means that while construction, operating and maintenance costs would fall by around 3.5bn, the net cost saving (revenues minus cost) would relatively small. Table A2.5 - Benefits of the HS2 Central Case Compared to a New Classic Line Quantified Costs and Benefits PV 2009 discount year and prices billion Transport User Benefits 6.7 Other Benefits (excl Carbon) 0.0 Net Transport Benefits 6.7 Capital Costs 3.0 Operating Costs 0.5 Total Costs 3.5 Revenues 2.9 Indirect Tax -0.3 Benefit Cost Ratio (Relative BCR of HS2 over Classic Line Alternative)

157 Appendix 2: Transport Economic Efficiency Tables A2.5.5 So upgrading the line to high speed would only have a relatively small cost to Government, but would generate significant benefits (time savings) to passengers on HS2. As a result the classic line alternative would have a worse business case than HS2 and the incremental case for high speed is very strong. A2.6 Reliability A2.6.1 A2.6.2 We have outlined in Chapter 3 how we have incorporated the potential benefits that high speed rail might deliver from improved reliability. The improvement in reliability is converted in to journey time savings, which are then subtracted from the actual journey times offered by HS2. This is a pragmatic approach to estimating a key benefit of high speed rail. However, while it is important that we estimate the benefits of reliability, we need to understand how significant the benefits are that it generates, and therefore how reliant the business case for HS2 is on these benefits. Table A2.6 outlines the results of a test which does not adjust journey times to include reliability benefits. Table A2.6 - Benefits from Improved Reliability Quantified Costs and Benefits PV 2009 discount year and prices billion Transport User Benefits 2.5 Other Benefits (excl Carbon) 0.0 Net Transport Benefits 2.5 Revenues 1.0 Indirect Tax -0.1 Benefit Cost Ratio (of HS2 without reliability benefits) 2.2 A2.6.3 Overall this reduces benefits by just under 10%, and would reduce the BCR to around 2.2 (excluding wider economic impacts). 157

158 Appendix 3: High Speed Rail and Spatial Patterns and Strategies in Cities and Regions

159 Appendix 3: High Speed Rail and Spatial Patterns and Strategies in Cities and Regions A3.1 Introduction A3.1.1 A3.1.2 The following paper summarises HS2 s understanding and interpretation of the literature on land use change as a result of transport interventions, and in particular the international experience of High Speed Rail. We are extremely grateful for the advice and comment of Roger Vickerman and Reg Harman in putting this paper together. However the findings and conclusions of this paper are those of HS2 alone. Transport can play an important role in defining the spatial patterns of economic activity across a city or region. It is often a key part of the strategies developed by regional and city authorities to shape the economy, environment and community within that area. A Spatial strategies may involve land use change which includes a wide range of different impacts. It may relate to relocation of households (both new houses and people moving home), changes in the type of business in an area, through to intensification of economic activity in that area. Changes and improvements in the transport network can support and perhaps encourage land use change through changing the accessibility of one area (or region) in relation to another. A more accessible location is often more attractive to both households and businesses who are keen to access employment, services and customers. And there is a feedback, with land use change affecting the strength of the case for some transport schemes. A3.1.4 Land use change can manifest itself in a variety of different ways, including: People moving house e.g. taking advantage of new and faster links to move to a larger house further from their job Firms may move to take advantage of new or improved transport opportunities to improve links between their customers or suppliers A3.1.5 A3.1.6 High Speed Rail would represent a major intervention which could lead to land use change at a local, regional and even national level. It has the potential to focus economic activity in the vicinity of a station (and the surrounding city) which acts as a node for both regional and national networks. This could trigger redistribution of activity from within the region and across the country. It is therefore important to consider the role of high speed rail in changing the spatial patterns and the role of high speed rail within wider strategies. This appendix considers what such impacts might be and what evidence exists. It concludes that the key for a high speed rail station being a catalyst for significant local and regional development is the integration of that station into a coherent wider spatial strategy for the city or region. However it also notes that this will not be a win-win conclusion. Some areas within a wider region may lose out, and it is possible a region itself may lose with some activity encouraged to relocate towards London. Whether such impacts materialise and how significant they are will depend on the economic structure of the cities, as well as the actions of regional and local planning authorities. 159

160 HS2 Demand Model Analysis A3.2 Why Does Spatial Impact (Land Use Change) Matter? A3.2.1 A3.2.2 A3.2.3 A3.2.4 A3.2.5 A3.2.6 Land use patterns are determined by a multiplicity of decisions taken by many different agents. A firm when choosing where to locate will consider many factors, including the price and availability of suitable buildings, labour supply and skills base, and access to markets to sell their product. Households choosing a home may trade off access to jobs (and the associated wage of those jobs) against the size of house, attractiveness of an area, even the quality of local schools. Transport affects a number of these factors, particularly the accessibility of jobs (and labour supply), goods and services and customers. Changes in the transport network, both in terms of the connectivity and efficiency of that network, can affect location decisions and result in land use change. However transport factors are more likely to affect where firms and households relocate, once the decision to move has been made, than to initiate a decision to relocate. Even then, good transport links may be seen as a bonus rather than a critical factor in location decisions. At a local level improving connectivity and accessibility can encourage businesses to locate in the area, boosting the economy, increasing jobs and helping to regenerate depressed economies. However many studies point out that, while transport is generally a very important factor in this process, it is often other factors such as the local skills base that are also important in regeneration. Transport can support growth, but it rarely unlocks growth constraints on its own. At a regional level, improvements in transport may encourage the re-distribution of economic activity both within and across regions. A transport improvement may attract firms to relocate from other areas. This is to the benefit of the receiving area, but to the detriment of the area losing business. The net effect may still be positive where the transport scheme boosts productivity either through reducing business costs (e.g. time savings) or agglomeration impacts as a result of increased density of firms but there would clearly be winners and losers within this process. A region may gain from improved transport links encouraging firms to locate in that region, but the transport intervention may also encourage firms away (as well as towards) the region receiving that intervention. By improving links between (say) the West Midlands and London, firms in the West Midlands might have the opportunity to relocate in London, whilst continuing to serve existing customers in the West Midlands. Alternatively firms in London might expand into the West Midlands, taking market share from existing West Midlands firms. Whether such movements occur is likely to depend on the nature of the transport intervention and the economic geography of that area. So for example high speed rail has been demonstrated have most significant impacts on the service sector. Therefore the scope for relocation of firms across and between regions as well as the draw of London will be more significant for cities with a service sector based economy. 160

161 Appendix 3: High Speed Rail and Spatial Patterns and Strategies in Cities and Regions A3.2.7 A3.2.8 At a local level, these changes may be significant. They cannot be ignored by high speed rail, and the development of stations will need to take account of the spatial implications of these schemes. However at a national level there is a danger that these changes in spatial patterns represent movements of economic activity and jobs around the country (rather than adding to the overall job market). This may not mean there is no (net) impact on the productivity and prosperity of the national economy. If land use change leads to more clustering of firms and workers (say around stations on the rail network), then this will tend to boost agglomeration and deepen labour markets. Anything that reduces the barriers between firms, and between firms and their workers will tend to benefit the national economy. However the effect may be much more significant in specific local communities particularly where regeneration is facilitated. It seems unlikely that these impacts can be determined a priori without much more detailed work. A3.3 How Might HS2 Affect Land Use? A3.3.1 High speed rail would represent a step change in the connectivity between places served by the high speed network. This could have many effects, over a wide geographical area. For example: The investment in a high quality station could encourage localised regeneration, with investment making the station and potentially surrounding area more attractive. This is much more likely if it fits in with the city strategy, for both local transport planning and land-use planning. At a regional level, improved links (particularly to London) could encourage firms to relocate closer to a new high speed rail station with benefits to the areas close to the station, perhaps to the detriment of surrounding areas. At a national level, any increase in agglomeration (from intensified economic activity near the station) will boost productivity and therefore GDP. A3.3.2 A3.3.3 Whether these occur, and how significant they are will depend on the detailed design of the scheme even down to the quality and design of the final high speed rail stations. They will also depend crucially on the way high speed rail is integrated into the surrounding transport and economic networks. HS2 has not attempted to explicitly model these impacts. At this stage we have limited our analysis to a review of the experience of high speed rail in other countries in the development and regeneration of cities, in order to identify the likely direction of these impacts, and to understand what has and hasn t worked. This does not suggest that these impacts are not important or that they should not be modelled at a later stage of design (if appropriate). Rather it reflects a view that any modelling at this stage would be subject to significant uncertainty. 161

162 HS2 Demand Model Analysis A3.4 The Evidence of Land Use Change and HSR A3.4.1 There are examples where high speed rail has resulted in significant effects from across the world, but also many where those impacts have failed to materialise. Two of the most well known examples are that of Lille and Lyon. The Lille conurbation has seen significant regeneration since the opening of TGV Nord in Lille was a manufacturing city which suffered major decline during the 1960s but has since seen a major drive for growth led by the city council and the other conurbation municipalities, together with the Nord Pas de Calais regional council. Major development has occurred in the areas surrounding the station but there has also been substantial regeneration at a range of locations across the conurbation, linked by new transit lines. Lyon has seen the relocation of its commercial district across the city into to the area surrounding the new Part-Dieu station. This is now the focus for most regional (TER) rail services, strengthening the city s already strong role as the regional commercial centre but also providing good links to the TGV services for many other centres across the region. A3.4.2 A3.4.3 Examples where broadly similar benefits have been gained from redevelopment and upgraded local transport exist across continental Europe, including Zaragoza and Cordoba (Spain), Köln (Germany), Torino (Italy), Antwerpen (Belgium). However there have been some cases where a high speed rail connection has had very limited (and even negative) impacts. These include: Vendome, where despite plans for redevelopment of the area, the station is primarily used for commuting to Paris and has lead to very little economic development in the area Haute Picardie, where there has been relatively limited economic development and indeed use of the high speed rail station. A3.4.4 Lessons have been learned from these. The intermediate stations on the TGV link between Paris and Strasbourg have seen much more careful planning of local transport links to the nearest regional town, although even here there are big contrasts between the different locations. 162

163 Appendix 3: High Speed Rail and Spatial Patterns and Strategies in Cities and Regions A3.4.5 A3.4.6 A3.4.7 A3.4.8 A3.4.9 Most research into the impact of high speed rail on local and regional economies has focused on individual examples, such as those outlined above. The conclusions are often hard to generalise. However some common themes come through. An observation made by both Bonnafous (1987) and Willigers (2003) is that firms see high speed rail as a bonus. By giving confirmation of an address on the network and thus underwriting a sense of confidence in a region it helps to confirm a decision to locate in a particular area, but other factors determine that decision. This adds further evidence that simply building a new link or station is not sufficient to ensure success. Wider factors within the local and regional economy need to be addressed such as the skills base or local infrastructure. The examples of where high speed rail has been a success have often seen a close integration of policies on a wide range of local and spatial issues together with the construction of high speed rail to deliver the outcomes that were desired. Bonnafous (1987) also suggests that the TGV has encouraged regional firms to fill niche markets in Paris. In particular service sector and consultancy type firms build on a familiarity with dealing with small and medium sized firms to expand in to Parisian markets. But the opposite is not true, with Parisian firms focusing on large firms and international markets rather than expanding into markets around Lyon. This matches analysis in Harman (2006). In Japan, Sasaki et al (1997) suggest that high speed rail has the effect of dispersing investment and economic activity from the developed region towards the periphery. This result did not appear to be to the detriment of the developed region, but there might be negative effects for regions that were not connected to the core high speed network. In line with the general findings in the literature, Sasaki et al again suggests that while HSR may have an effect, other factors such as the productive capability and skills of a regional economy will also be important. They conclude that while HSR can help to redistribute economic activity it is unlikely to solve regional inequalities. Most recently Greengauge 21 considered the scope for wider economic impacts including the potential for land use change using a version of the DELTA model to model the impact of accessibility change on employment in different zones. They conclude wider economic impacts could add up to 20% benefits to the traditional transport appraisal. However the bulk of these impacts came from the conventional assessment of Wider Economic Impacts, and not changes in land use driven by high speed rail. A It is clear from the evidence available that high speed rail has the potential to have significant effects on land use and activity at a local and regional level. Whether these local and regional effects feed into economic benefits at a national level is unclear and there is a lack of evidence in this area. However regardless of what the impact is, it is clear that HSR has been most successful where it has formed a part of a wider package of measures. 163

164 HS2 Demand Model Analysis A3.5 Conclusions A3.5.1 A3.5.2 High speed rail would represent a step change in the connectivity and speed of the transport network. It would clearly have the potential to have significant impacts on the performance of regional economies, and the distribution and nature of economic activity across and between regions. The international experience shows that there are many reasons for the success or failure of individual high speed rail stations often specific to the local circumstances. However there are some consistent messages in this literature: Integration is Key Simply building a station or link to the high speed network is not enough. For success to be achieved the station has to be integrated into the wider strategic plans of local agencies, especially integration with the local transport network. There are many factors which are more important in regeneration than transport alone. It not surprising therefore that wider strategies on land use planning and even education and skills are needed to successfully integrate a station into the local and regional economy. Role as a hub Whilst not always the case, there are examples of success where the high speed rail station also has hub-like connectivity with good links to the local/regional rail network as well as the high speed network. Thus the station becomes a focus for the regional economy as well as a wider market supported by high speed. This is not win-win Although there are many examples where growth and regeneration has been delivered around a high speed rail station, this may be to the detriment of the surrounding region. Economic activity tends to move away from the peripheries and towards the high speed station or hub. The extent to which this happens is not clear, nor the key factors that may affect it. One might hypothesise the greater degree of competition there is between firms in the periphery and around the station, the greater the loss to the surrounding area, but more research is needed here. A3.5.3 It is clear from international experience that for high speed rail to deliver benefits at a local and regional level there needs to be clear and strongly led spatial and economic planning strategies. The appropriate design and connectivity of the high speed network will be important, but perhaps more important is the integration of that network within the local and regional strategies. Where high speed rail stations have been successful in driving regeneration and economic development, there has been a clear long term vision for the city, and how high speed rail fits within that vision. Strong leadership at a local level is needed to ensure the effective integration of local priorities with national. 164

165 Appendix 3: High Speed Rail and Spatial Patterns and Strategies in Cities and Regions A3.5.4 A3.5.5 Wider policy formulation and implementation is also needed to ensure that (a) land use planning facilitates land use change and (b) other policies are in place to ensure the necessary skills and other factors exist to take advantage of this opportunity. Integration into the local transport network as part of this will boost the case, with a suggestion that railway hubs help to integrate local, regional and large scale markets providing a focus to activity. The impact of a high speed rail station can clearly be significant at a local level. They therefore play an important role within regional and local spatial strategies. However the degree to which they boost productivity at a national level is far less certain. Such local and regional impacts are likely to reflect a redistribution of economic activity rather than new activity. They are in essence the manifestation of time savings that are already captured in transport appraisal. A3.6 References Bonnafous (1987), Regional Impacts of the TGV, Transportation vol. 14 Harman (2006), High speed trains and the development and regeneration of cities, Greengauge 21 ( Sasaki, Okaski and Ando (1997), High-speed rail transit impact on regional systems: does the Shinkansen contribute to dispersion?, Annals of Regional Science Segal (2009), A Strategy for a High Speed Rail Network in Britain, Paper presented to the European Transport Conference Vickerman (2009), Indirect and Wider Economic Impacts of High Speed Rail, in de Rus et al (2009) Economic Analysis of High Speed Rail in Europe, Fundacion BBVA Vickerman (1997), High-speed rail in Europe: experience and issues for future development, The Annals of Regional Science Willigers (2003), High speed railway developments and corporate location decisions, Paper presented at the 43rd ERSA Congress, Jyväskylä 165

166 Appendix 4: Service Specification for Wider Network Test

167 Appendix 4: Service Specification for Wider Network Tests A4.1.1 A4.1.2 A4.1.3 A4.1.4 This appendix contains the detailed service specifications we used for the demand modelling runs informing the analysis behind the Longer Term Strategy (Chapter 6 of the main report). Chapter 11 describes our approach in detail. We calculated journey times for routes on the three networks as well as for the extensions to Manchester and Leeds for modelling purposes. These are based on assumed speed profiles and route distances and are generally conservative estimates. The benefits from journey time savings can be very substantial, but we have avoided the temptation to assume the best. In reality, initial optimum journey times will typically be restricted by a number of factors, such as tunnelling prompted by specific environmental mitigation, linespeed restrictions to reduce noise impacts on the local population and by constrained speeds on urban route sections. The figures below graphically represent the journey times and service patterns that we assumed under each of the five scenarios. These are not optimised but rather reflect a plausible service within the overall capacity of the line. They have not been subjected to the same level of scrutiny as those developed for HS2. As explained in Chapter 11 the starting point and reference cases for the two extension scenarios was the Day One scenario while the three wider networks are assessed against the do minimum scenario. In designing service patterns there will always be a delicate balance to be struck between on the one hand stopping trains to widen accessibilty and improve connections, and on the other reducing the number of stops to achieve better journey times. As explained in Chapter 11, we have undertaken some analysis to improve this trade off. We do not purport, however, to have found the optimal balance in this exercise. 167

168 HS2 Demand Model Analysis Inverse A Service Specification Euston Birmingham Central..... Old Oak Common Nottingham Parkway Birmingham interchange South Yorkshire Parkway Birmingham Central Liverpool Central 0 49 Manchester Central Manchester Central Liverpool Central Leeds Central Nottingham Parkway Leeds Parkway South Yorkshire Parkway Teesside Parkway Leeds Central Newcastle Central West Yorkshire Parkway Preston Parkway Teesside Parkway Carstairs Interchange split Newcastle Central Glasgow Central Preston Parkway Edinburgh Central Carstairs Interchange split split Glasgow Central Edinburgh Central split

169 Appendix 4: Service Specification for Wider Network Tests Reverse E Service Specification Euston Birmingham Central..... Old Oak Common Nottingham Parkway Birmingham interchange South Yorkshire Parkway Birmingham Central Liverpool Central 0 49 Manchester Central Manchester Central Stafford Leeds Central Crewe West Yorkshire Parkway Warrington Bank Quay Teesside Parkway Runcorn Newcastle Central Liverpool Central Newcastle Interchange Nottingham Parkway Hawick Parkway split South Yorkshire Parkway Glasgow Central Leeds Central Edinburgh Central West Yorkshire Parkway Teesside Parkway Newcastle Central Newcastle Interchange Wigan North Western Preston Parkway Hawick Parkway split split Glasgow Central Edinburgh Central Hybrid Services HS Captive Services split

170 HS2 Demand Model Analysis Reverse S Service Specification Euston Birmingham Central. Old Oak Common Manchester Central Birmingham interchange Leeds Central Birmingham Central West Yorkshire Parkway Manchester Central Teesside Parkway Stafford Newcastle Central Crewe Hawick Parkway Warrington Bank Quay Edinburgh Central Runcorn Liverpool Central Leeds Central West Yorkshire Parkway Teesside Parkway Newcastle Central Newcastle Interchange Wigan North Western Preston Hawick Parkway split split Glasgow Central Edinburgh Central Hybrid Services HS Captive Services

171 Appendix 4: Service Specification for Wider Network Tests Manchester Extensions Service Specification Euston Birmingham Central Old Oak Common Manchester Central Birmingham interchange Birmingham Central 0:49 Stafford Crewe Manchester Piccadilly Warrington Bank Quay :20 Runcorn Liverpool Lime Street :37 1:50 Wigan North Western Preston Glasgow Central : Hybrid Services HS Captive Services Peak Hour Only 0:54 171

172 HS2 Demand Model Analysis Leeds Extension Service Specification and Background Data Hybrid Services HS Captive Services Peak Hour Only These Services are unchanged from Day One scenario Additional Services on Eastern Route Euston Euston Old Oak Common Old Oak Common Birmingham interchange Birmingham interchange Birmingham Central Birmingham Central 0:49 Stafford Nottingham Parkway Crewe South Yorkshire Parkway Wilmslow Leeds Central 1:15 1:20 1:26 1:35 1:05 Stockport West Yorkshire Parkway Manchester Piccadilly Teesside Parkway :40 1:44 Warrington Bank Quay Newcastle Central Runcorn :37 Liverpool Lime Street :50 Wigan North Western Preston Glasgow Central :48 4:00 2:20 172