High-speed rail and air transport competition and cooperation: A vertical differentiation approach

This paper considers vertical differentiation between air transport and high-speed rail (HSR) with different ranges of travel distance to analyze the air-HSR competition effects on fares, traffic volumes and welfare, as well as the conditions under which air-HSR cooperation is welfare-enhancing. The analysis is conducted in a hub-and-spoke network with a network carrier, an HSR operator, and a spoke airline, taking into account potential hub airport capacity constraint. We find that air-HSR competition in the connecting market may result in the network airline charging an excessively high price in the HSR-inaccessible market. This effect is present even when the HSR-inaccessible route is a duopoly-airline market. On the other hand, air-HSR cooperation increases fares in the connecting market, and an improvement in rail speed or air-HSR connecting time reduces airfare on the routes where HSR and the airline compete. When the airline cannot serve all the markets due to limited hub airport capacity, it would withdraw from the market in which it has less competitive advantage over HSR. Finally, air-HSR cooperation is more likely to be welfare-improving when the hub airport is capacity constrained, and when either air transport or HSR exhibits strong economies of traffic density.     

The future relations between air and rail transport in an island country

This paper proposes a bi-level passenger transport market model taking into account competition between air and high-speed rail (HSR) in a domestic market. The paper discusses the characteristics of the relationship between market share and connectivity in domestic and international markets. The result suggests that because of the dominance of HSR in the domestic market, when connectivity between air and HSR is good, international passenger’s welfare can be improved. Finally, when considering profitability of the players, there is an incentive for airlines to cooperate with HSR, but there is no incentive for HSR to cooperate with airlines.     

Help or hindrance? The travel,energy and carbon impacts of highly automated vehicles

Experts predict that new automobiles will be capable of driving themselves under limited conditions within 5–10 years, and under most conditions within 10–20 years. Automation may affect road vehicle energy consumption and greenhouse gas (GHG) emissions in a host of ways, positive and negative, by causing changes in travel demand, vehicle design, vehicle operating profiles, and choices of fuels. In this paper, we identify specific mechanisms through which automation may affect travel and energy demand and resulting GHG emissions and bring them together using a coherent energy decomposition framework. We review the literature for estimates of the energy impacts of each mechanism and, where the literature is lacking, develop our own estimates using engineering and economic analysis. We consider how widely applicable each mechanism is, and quantify the potential impact of each mechanism on a common basis: the percentage change it is expected to cause in total GHG emissions from light-duty or heavy-duty vehicles in the U.S. Our primary focus is travel related energy consumption and emissions, since potential lifecycle impacts are generally smaller in magnitude. We explore the net effects of automation on emissions through several illustrative scenarios, finding that automation might plausibly reduce road transport GHG emissions and energy use by nearly half – or nearly double them – depending on which effects come to dominate. We also find that many potential energy-reduction benefits may be realized through partial automation, while the major energy/emission downside risks appear more likely at full automation. We close by presenting some implications for policymakers and identifying priority areas for further research.     

Achieving environmental sustainability beyond technological improvements: Potential role of high-speed rail in the United States of America

In order to reduce energy use and cut emissions that contribute to climate change, countries need to radically reinvent their fossil-fuel intensive transportation systems. As a major consumer of energy and contributor to greenhouse gas (GHG) emissions, the U.S. transportation sector faces extraordinary challenges in the twenty-first century. Transportation in the U.S. depends heavily on fossil-fuel dependent cars and planes to the near exclusion of more energy-efficient electric trains. In order to address this concern, some policy makers refer to “technological optimism” which seeks no systemic change but instead focuses on employing technology to reduce the energy demand and environmental impact of the status quo. On the other hand, some researchers suggest a systematic paradigm shift away from cars and planes to intermodal systems that improve the sustainability of the system as a whole. High-speed rail (HSR) is arguably such an investment that can further this shift and help to achieve a more diversified and balanced transportation system. In this respect, by largely examining the role of the U.S. cars and planes “culture” in the economy, this paper elaborates on how building a HSR system may help U.S. advance towards environmental sustainability in transportation, make a break from the status quo, and create a more balanced, multimodal transportation system that will improve the quality and efficiency of travel.     

Well-to-wheel assessment of natural gas vehicles and their fuel supply infrastructures – Perspectives on gas in transport in Denmark

In this paper, potential natural gas and renewable natural gas supply pathways and natural gas vehicles (NGVs) have been selected and evaluated with regards to well-to-wheel energy expended, greenhouse gas (GHG) emissions, and regulated (air pollutant) emissions. The vehicles included in the evaluation are passenger cars, light-duty vehicles (LDVs), and heavy-duty vehicles (HDVs) for road-transport applications, and a short-range passenger vessel for maritime transport applications. The results show that, compared to conventional fuels, in both transport applications and for all vehicle classes, the use of compressed and liquefied natural gas has a 15–27% GHG emissions reduction effect per km travel. The effect becomes large, 81–211%, when compressed and liquefied renewable natural gas are used instead. The results are sensitive to the type and source of feedstock used, the type of vehicle engine, assumed methane leakage and methane slip, and the allocated energy and environmental digestate credits, in each pathway. In maritime applications, the use of liquefied natural gas and renewable natural gas instead of low sulfur marine fuels results in a 60–100% SOx and 90–96% PM emissions reduction. A 1% methane slip from a dedicated LNG passenger vessel results, on average, in 8.5% increase in net GHG emissions.     

Planning for economic and environmental resilience

Climate protection will require major reductions in GHG emissions from all sectors of the economy, including the transportation sector. Slowing growth in vehicle miles traveled (VMT) will be necessary for reducing transportation GHG emissions, even with major breakthroughs in vehicle technologies and low-carbon fuels (Winkelman et al., 2009). The Center for Clean Air Policy (CCAP) supports market-based policy approaches that minimize costs and maximize benefits. Our research indicates that significant GHG reductions can be achieved through smart growth and travel efficiency measures that increase accessibility, improve travel choices and make optimum use of existing infrastructure. Moreover, we find such measures can deliver compelling economic benefits, including avoided infrastructure costs, leveraged private investment, increased local tax revenues and consumer vehicle ownership and operating cost savings (Winkelman et al., 2009).As a society, what we build – where and how – has a tremendous impact on our carbon footprint, from building design to transportation infrastructure and land-use patterns. The empirical and modeling evidence is clear – people drive less in locations with efficient land use patterns, high quality travel choices and reinforcing policies and incentives (Ewing et al., 2008). It is also clear that there is growing and unmet market demand for walkable communities, reinforced by demographic shifts and higher fuel prices (Leinberger, 2006, Nelson, 2007). Transportation policy in the United States must rise to meet this demand for more travel choices and more livable communities.The academic, ideological and political debates about the level of GHG reductions and penetration rates that can or should be achieved via smart growth and pricing on the one hand, or measures such as ‘eco-driving’ and signal optimization on the other, have served their purpose: we know which policies are ‘directionally correct’ – policies that reduce GHG emissions even though we may not know the scope of those reductions. Now is the time to implement directionally correct policies, assess what works best where, and refine policy based on the results. It is a framework that CCAP calls “Do. Measure. Learn.”The Federal government is poised to spend $500 billion on transportation (Committee on Transportation and Infrastructure, 2009). CCAP encourages Congress to “Ask the Climate Question” – will our transportation investments help reduce GHG emissions or exacerbate the problem? Will they help increase our resilience to climate change impacts or increase our vulnerability? And, while we’re at it, will our investment foster energy security, livable communities and a vibrant economy? Federal transportation and climate policies should empower communities to implement locally-determined travel efficiency solutions by providing appropriate funding, tools and technical support.     

Airline network choice and market coverage under high-speed rail competition

While the existing literature has focused on the short-term impacts, this paper investigates the long-term impacts of high-speed rail (HSR) competition on airlines. An analytical model is developed to study how an airline may change its network and market coverage when facing HSR competition on trunk routes. We show that prior to HSR competition, an airline is more likely to adopt a fully-connected network and cover fewer fringe markets if the trunk market is large. Under HSR competition, the airline will, for a given network structure, have a greater incentive to cover more fringe (regional or foreign) markets if the trunk market is large, or the airline network is close to hub-and-spoke. Further, the airline will, for any given market coverage, move towards a hub-and-spoke network when the trunk market is large, or the number of fringe markets covered by the airline network is large. Both effects are more prominent when the decreasing rate of airline density economies is large. We further show that HSR competition can induce the airline to adopt network structure and market coverage that are closer to the socially optimal ones, thereby suggesting a new source of welfare gain from HSR based on its long-term impacts on airlines. Implications for operators, policy makers and specific countries (such as China) are also discussed.     

Multiple hub network and high-speed railway: Connectivity,gateway, and airport leakage

This paper considers the relation between the role of airport as gateway (inter–intra transit airport) and the connectivity between air transport and high-speed rail (HSR) transport to discuss the possibility of a multiple gateway system with HSR. We deal with both international and domestic transport markets in the model analysis. In the international markets, only airlines compete against each other, while in the domestic market airlines and HSR compete against each other. The results suggest that the improvement of connectivity between air and HSR at the airport increases its international passengers, and therefore, that strengthens its role as gateway, for example, gathering more inter–intra transit passengers. However, the results also suggest that the demand of the area which the airport belongs to affects the role of airport as gateway.     

Optimal development of alternative fuel station networks considering node capacity restrictions

A potential solution to reduce greenhouse gas (GHG) emissions in the transport sector is the use of alternative fuel vehicles (AFV). As global GHG emission standards have been in place for passenger cars for several years, infrastructure modelling for new AFV is an established topic. However, as the regulatory focus shifts towards heavy-duty vehicles (HDV), the market diffusion of AFV-HDV will increase as will planning the relevant AFV infrastructure for HDV. Existing modelling approaches need to be adapted, because the energy demand per individual refill increases significantly for HDV and there are regulatory as well as technical limitations for alternative fuel station (AFS) capacities at the same time. While the current research takes capacity restrictions for single stations into account, capacity limits for locations (i.e. nodes) – the places where refuelling stations are built such as highway entries, exits or intersections – are not yet considered. We extend existing models in this respect and introduce an optimal development for AFS considering (station) location capacity restrictions. The proposed method is applied to a case study of a potential fuel cell heavy-duty vehicle AFS network. We find that the location capacity limit has a major impact on the number of stations required, station utilization and station portfolio variety.     

Hydrogen refueling station networks for heavy-duty vehicles in future power systems

A potential solution to reduce greenhouse gas (GHG) emissions in the transport sector is to use alternatively fueled vehicles (AFV). Heavy-duty vehicles (HDV) emit a large share of GHG emissions in the transport sector and are therefore the subject of growing attention from global regulators. Fuel cell and green hydrogen technologies are a promising option to decarbonize HDVs, as their fast refueling and long vehicle ranges are consistent with current logistic operational requirements. Moreover, the application of green hydrogen in transport could enable more effective integration of renewable energies (RE) across different energy sectors. This paper explores the interplay between HDV Hydrogen Refueling Stations (HRS) that produce hydrogen locally and the power system by combining an infrastructure location planning model and an electricity system optimization model that takes grid expansion options into account. Two scenarios – one sizing refueling stations to support the power system and one sizing them independently of it – are assessed regarding their impacts on the total annual electricity system costs, regional RE integration and the levelized cost of hydrogen (LCOH). The impacts are calculated based on locational marginal pricing for 2050. Depending on the integration scenario, we find average LCOH of between 4.83 euro/kg and 5.36 euro/kg, for which nodal electricity prices are the main determining factor as well as a strong difference in LCOH between north and south Germany. Adding HDV-HRS incurs power transmission expansion as well as higher power supply costs as the total power demand increases. From a system perspective, investing in HDV-HRS in symbiosis with the power system rather than independently promises cost savings of around seven billion euros per annum. We therefore conclude that the co-optimization of multiple energy sectors is important for investment planning and has the potential to exploit synergies.     

Forecasting demand for high speed rail

It is sometimes argued that standard state-of-practice logit-based models cannot forecast the demand for substantially reduced travel times, for instance due to High Speed Rail (HSR). The present paper investigates this issue by reviewing the literature on travel time elasticities for long distance rail travel and comparing these with elasticities observed when new HSR lines have opened. This paper also validates the Swedish long distance model, Sampers, and its forecast demand for a proposed new HSR, using aggregate data revealing how the air–rail modal split varies with the difference in generalized travel time between rail and air. The Sampers long distance model is also compared to a newly developed model applying Box–Cox transformations. The paper contributes to the empirical literature on long distance travel, long distance elasticities and HSR passenger demand forecasts. Results indicate that the Sampers model is indeed able to predict the demand for HSR reasonably well. The new non-linear model has even better model fit and also slightly higher elasticities.     

An exploration of the competitive relationship between intercity transport systems

A suitable model that enables the analysis of dynamic relationships between transport systems is important for managers to make real-time reaction strategies. This study proposes an autoregressive distributed lag modeling approach that can point a way to interpret the long- and short-term relationships between intercity transport systems. To test the applicability of the approach with regard to evaluating the dynamic competitive relationships between intercity transport systems, an empirical study sample is adopted in evaluating competition between high-speed rail (HSR) and intercity bus services. The results indicate that HSR has a long-run impact on intercity bus transport and the intercity bus transport market is positively affected by its previous operations and negatively influenced by the previous performance of HSR. However, in the short-run, the current period performance of HSR positively affects the intercity bus transport market.     

Time-based life-cycle assessment for environmental policymaking: Greenhouse gas reduction goals and public transit

As decision-makers increasingly embrace life-cycle assessment (LCA) and target transportation services for regional environmental goals, it becomes imperative that outcomes from changes to transportation infrastructure systems are accurately estimated. Greenhouse gas (GHG) reduction policies have created interest in better understanding how public transit systems reduce emissions. Yet the use of average emission factors (e.g., grams CO₂e per distance traveled) persists as the state-of-the-art masking the variations in emissions across time, and confounding the ability to accurately estimate the environmental effects from changes to transit infrastructure and travel behavior. An LCA is developed of the Expo light rail line and a competing car trip (in Los Angeles, California) that includes vehicle, infrastructure, and energy production processes, in addition to propulsion. When results are normalized per passenger kilometer traveled (PKT), life-cycle processes increase energy use and GHG emissions up to 83%, and up to 690% for smog and respiratory impact potentials. However, the use of a time-independent PKT normalization obfuscates a decision-maker’s ability to understand whether the deployment of a transit system reduces emissions below a future year policy target (e.g., 80% of 1990 emissions by 2050). The year-by-year marginal effects of the decision to deploy the Expo line are developed including reductions in automobile travel. The time-based marginal results provide clearer explanations for how environmental effects in a region change and the critical life-cycle processes that should be targeted to achieve policy targets. It shows when environmental impacts payback and how much reduction is achieved by a policy-specified future year.     

Co-benefits of low carbon passenger transport actions in Indian cities: Case study of Ahmedabad

Rising population, income and urbanization are increasing urban passenger transport demand in India. Energy and emissions intensities associated with conventional transport are no longer sustainable vis-a-vis energy security, air quality and climate change. Cities are seeking transport roadmaps that jointly mitigate these risks. Roadmaps vary across cities, but approach to delineate actions is common: (i) ‘representative vision’ that articulates long-term goals, (ii) methods for comparative scenarios assessment, and (iii) quantification of co-benefits to prioritize actions. This paper illustrates application of quantitative modeling to assess development and environmental co-benefits for Ahmedabad city. The paper constructs two transport scenarios spanning till 2035. The bifurcating themes are: (i) Business-as-Usual (BAU) and Low Carbon Scenario (LCS). The quantitative assessment using Extended Snapshot (ExSS) Model shows that transport activity shall result in four-fold increase in energy demand under BAU from 2010 to 2035. Three key contributors to CO₂ mitigation under LCS in merit order are: (i) fuel switch, including decarbonized electricity, (ii) modal shift, and (iii) substitution of travel demand. Scenarios analysis shows that LCS improves energy security by reducing oil demand and also delivers air quality co-benefits – reducing 74% NOx and 83% PM_2.5 from the passenger transport sector compared to BAU in 2035. Finally, the paper argues that cities in developing countries can leverage carbon finance to develop sustainable and low carbon mobility plans that prevent adverse infrastructure and behavioral lock-ins and prompt low carbon development.     

The effects of physical activity on greenhouse gas emissions for common transport modes in European countries

This paper applies a life cycle methodology to estimate activity-related contributions of transport modes to GHG emissions. The methodology uses national input–output tables, environmental accounts, household budget data and nutritional data to derive food-sector GHG coefficients of consumption for ten European countries. The food energy requirements for each mode of transport are estimated taking account of the modal activity level and energy requirements. Typical national food energy-related emissions for walking, cycling, and driving ranged from 25.6 to 77.3 gCO₂-eq/pass.km, 10.4–31.4 gCO₂-eq/pass.km and 1.7–5.2 gCO₂-eq/pass.km; passenger transport was found to result in no food-related emissions above those for a resting individual. Emissions vary between countries depending on the emissions intensities of their energy sectors as well as food prices and average body weights. A life cycle assessment of modal emissions in the UK is undertaken using the food-energy emissions intensities estimated and car travel was found to have the highest emissions intensity, followed by bus, cycling and walking.     

Transport infrastructure costs in low-carbon pathways

The rate and manner in which transport infrastructure (e.g. roads, railway tracks, airports) is deployed, will play an important role in determining energy demand, greenhouse gas emissions and the economic impact of the transport sector. This paper describes an exercise where the costs of infrastructure deployment for the transport sector have been incorporated into the IMACLIM-R Global E3 IAM. In addition to adding these costs, the modelling of the criteria for the deployment of infrastructure for roads has also been improved. It is found that this model recalibration results in a more accurate baseline as compared to historically observed data (2001–2013) for investments in energy demand, road infrastructure, and passenger kilometers travelled. Regarding macroeconomic effects, it is found that the imposition of a carbon emission trajectory to 2100 cause GDP to decrease relative to the newly calibrated baseline – this is a standard IAM result. However, when the deployment of infrastructure for roads and air travel is further constrained, the GDP loss is less than with a fixed carbon emission trajectory only. This is because early restriction of infrastructure for roads and air travel allows an expansion of public transport infrastructure which is adequate to meet low-carbon transport service demand whereas when less public transport infrastructure is available, more costly mitigation investments must be made in other parts of the economy. This suggests that restricting infrastructure deployment as a complementary policy to carbon pricing, lowers the cost of mitigation.     

Pathways for GHG emission reduction in Norwegian road transport sector: Perspective on consumption of passenger car transport and electricity mix

Electrification of the transport sector is considered as a solution to reduce greenhouse gases (GHGs) emissions and achieve sustainable mobility. Specifically in the case of electrification of passenger vehicles, various industrial and policy initiatives have been introduced. In this article, we present and assess three approaches – pro-technology, pro-simplicity and mix (of the aforementioned approaches) – to achieve target emission reductions in the Norwegian road transport sector. We also assess the influence of including ‘Guarantee of Origin’ certification for the electricity production in accounting for typical consumption electricity mix in Norway.Results show that for the same reductions in tail-pipe GHG emissions, pro-technology, pro-simplicity, and the mix scenario offer 22%, 29% and 28% reduction in the life cycle GHG emissions respectively, compared to the reference scenario in year 2020. However, the pro-simplicity scenario requires 25% reduction in vehicle-km driven compared to the pro-technology scenario, which provides the same passenger car mobility as in the reference case. When the GHG intensity of the electricity mix used to power EVs is corrected to account for actual consumption mix in Norway, a 13% reduction in the net GHG benefit of pro-technology scenario is observed.     

A Review of Ex-Post Evidence for Mode Substitution and Induced Demand Following the Introduction of High-Speed Rail

ABSTRACT

To date, relatively little is known about the nature of the demand for high-speed rail (HSR) soon after inauguration of the services, despite close to 50-year experience of HSR operation and 17 166?km of HSR network around the world. This is a real lacuna given the scale of HSR construction around the world, the amount of resources committed to it, the desired accessibility, economic and environmental effects associated with HSR development and the relatively poor track record of forecasting demand for HSR services. Focusing on mode substitution and induced demand effects, this review aims to fill the gap in knowledge about the ex-post demand for HSR services in order to facilitate a learning process for the planning of the future HSR network. Although there is not much evidence on the demand for HSR services and existing evidence is largely influenced by route-specific characteristics, a methodological limitation that must be acknowledged, the evidence presented allows a better characterisation of HSR as a mode of transport. The review shows that the demand for HSR a few years after inauguration is about 10–20% induced demand and the rest is attributed to mode substitution. In terms of mode substitution, in most cases the majority of HSR passengers have used the conventional rail before. Substitution from aircraft, car and coach is generally more modest.     

High-speed rail's potential for the reduction of carbon dioxide emissions from short haul aviation: a longitudinal study of modal substitution from an energy generation and renewable energy perspective

Abstract

This paper quantifies and evaluates, utilising a ‘bottom-up’ approach, the effect on CO₂ emissions of a modal shift from short-haul air travel to high-speed rail (HSR), based on projected passenger movements, between Sydney and Melbourne, Australia during the period 2010–2030. To date, peer-reviewed studies assessing the CO₂ emissions from these competing modes of high-speed transportation have been restricted principally to a cross-sectional assessment, with a Eurocentric bias. This present comparative study seeks to address a gap in the literature by assessing, longitudinally, the CO₂ emissions associated with the proposed operation of HSR against the ‘business-as-usual’ air scenario between Sydney and Melbourne. Under the assumed 50/50 modal shift, and the Australian government's current renewable electricity target, an annual reduction in CO₂ emissions of approximately 14% could be achieved when compared with a ‘business-as-usual’ air scenario. This percentage reduction represents a 62 kt reduction in base year, 2010, and a 114 kt reduction in the final year, 2030. In total, the overall reduction achieved by such a modal shift, under the assumed conditions, during the period 2010–2030, equates to approximately 1.87 Mt of CO₂. Importantly, if the electrical energy supply for HSR operations was further ‘decarbonised’, then it follows that a greater emission reduction would be achieved.     

Comparing the impact of future airline network change on emissions in India and the United States

In this paper we use simulation to analyze how flight routing network structure may change in different world regions, and how this might impact future traffic growth and emissions. We compare models of the domestic Indian and US air transportation systems, representing developing and mature air transportation systems respectively. We explicitly model passenger and airline decision-making, capturing passenger demand effects and airline operational responses, including airline network change. The models are applied to simulate air transportation system growth for networks of 49 airports in each country from 2005 to 2050. In India, the percentage of connecting passengers simulated decreases significantly (from over 40% in 2005 to under 10% in 2050), indicating that a shift in network structure towards increased point-to-point routing can be expected. In contrast, very little network change is simulated for the US airport set modeled. The simulated impact of network change on system CO₂ emissions is very small, although in the case of India it could enable a large increase in demand, and therefore a significant reduction in emissions per passenger (by nearly 25%). NO_x emissions at major hub airports are also estimated, and could initially reduce relative to a case in which network change is not simulated (by nearly 25% in the case of Mumbai in 2025). This effect, however, is significantly reduced by 2050 because of frequency competition effects. We conclude that network effects are important when estimating CO₂ emissions per passenger and local air quality effects at hub airports in developing air transportation systems.