Evaluating locational accessibility to the US air transportation system

Although there are hundreds of airports that support commercial air passenger traffic in the United States (US), not all areas are equivalently served by the commercial air transportation system. Locations in the US differ with respect to their level of access to the commercial air network and their overall accessibility within the system. Given the complexity of the domestic commercial air passenger network and supporting infrastructure, past research has only been able to provide a limited assessment of locational accessibility within the United States. To address these complexities, this paper proposes a new metric that incorporates measures of access to air transport as well as accessibility within air transportation networks. Using a comprehensive dataset on scheduled airline service, the developed approach is then applied to the US domestic commercial passenger air transportation network to explore geographic differentials in accessibility. Results suggest marked differences between core-based statistical areas throughout the US.     

A system dynamics model of CO2 mitigation in China’s inter-city passenger transport

Mitigation of greenhouse gas emissions from transportation has become increasingly important and challenging especially for developing countries. This paper takes the inter-city passenger transport in China as a case, and develops a system dynamics model for policy assessment and CO₂ mitigation potential analysis. It is found that the future demand for China’s inter-city passenger transport is expected to be large, with the turnover volume growing at a rate of 9% per annum and amounting to 6600 billion p-km in 2020. Major emissions reduction potential exists in inter-city passenger transport. In 2020, comparing to the case without any specific policies stressing mitigation, the reduction of CO₂ emissions ranges from 26% to 32% under those scenarios with policy controls. Sensitivity analysis reveals that the CO₂ mitigation will be best achieved by accelerating the development of railway network, together with slowing down the extension of highway network and imposing fuel taxes.     

An optimization model of energy and transportation systems: Assessing the high-speed rail impacts in the United States

This paper presents a long-term investment planning model that co-optimizes infrastructure investments and operations across transportation and electric infrastructure systems for meeting the energy and transportation needs in the United States. The developed passenger transportation model is integrated within the modeling framework of a National Long-term Energy and Transportation Planning (NETPLAN) software, and the model is applied to investigate the impact of high-speed rail (HSR) investments on interstate passenger transportation portfolio, fuel and electricity consumption, and 40-year cost and carbon dioxide (CO₂) emissions. The results show that there are feasible scenarios under which significant HSR penetration can be achieved, leading to reasonable decrease in national long-term CO₂ emissions and costs. At higher HSR penetration of approximately 30% relative to no HSR in the portfolio promises a 40-year cost savings of up to $0.63 T, gasoline and jet fuel consumption reduction of up to 34% for interstate passenger trips, CO₂ emissions reduction by about 0.8 billion short tons, and increased resilience against petroleum price shocks. Additionally, sensitivity studies with respect to light-duty vehicle mode share reveal that in order to realize such long-term cost and emission benefits, a change in the passenger mode choice is essential to ensure higher ridership for HSR.     

枢纽机场航线网络优化研究

枢纽机场航线网络优化主要解决由于航线网络结构与功能定位不匹配而导致的机场连通性低、航线网络同质化竞争严重、运行效率低下的问题。通过改进引力模型对城市对间的客流量进行预测,以此为预测的客流量为依据之一,以提高机场连通性为目的,构建航线网络优化模型,并进行求解。实现提高枢纽机场连通性、构建符合功能定位的层级网络的目标。并以位于我国中部,具有"连接南北,贯穿东西"地理优势的西安咸阳国际机场为例进行分析。由于国际航线受客观因素较多,本文主要研究国内客运航线,国际及货运不在本文研究之列。     

Congestion spill effects of Heathrow and Frankfurt airports on connection traffic in European and Gulf hub airports

We develop two stage fixed-effects single-spill and double-spill models for congestion connection spills of London Heathrow and Frankfurt airports on 9 hub airports in Europe and the Gulf. Our panel data covers connection traffic from 1997 to 2013 for Heathrow and 1997 to 2011 for Frankfurt. The single-spill results support strongly that the connection spills from Heathrow’s capacity limitations do strengthen competing hub airports of major alliance groups and to a lesser degree one Gulf hub. The double-spill model for Heathrow and Frankfurt shows nearly asymmetric overall spill characteristics between the two airports. Our results underline the influence of airline network strategies on congestion spills as European airline networks are shaped by alliances and umbrella mergers. Thus, the airline network perspective in airport capacity expansion decisions needs to play a greater role, as indicated by our asymmetric results for overall spill effects between Heathrow and Frankfurt airports.     

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.     

Effects of high-speed rail and airline cooperation under hub airport capacity constraint

This paper analyzes the effects of cooperation between a hub-and-spoke airline and a high-speed rail (HSR) operator when the hub airport may be capacity-constrained. We find that such cooperation reduces traffic in markets where prior modal competition occurs, but may increase traffic in other markets of the network. The cooperation improves welfare, independent of whether or not the hub capacity is constrained, as long as the modal substitutability in the overlapping markets is low. However, if the modal substitutability is high, then hub capacity plays an important role in assessing the welfare impact: If the hub airports are significantly capacity-constrained, the cooperation improves welfare; otherwise, it is likely welfare reducing. Through simulations we further study the welfare effects of modal asymmetries in the demands and costs, heterogeneous passenger types, and economies of traffic density. Our analysis shows that the economies of traffic density alone cannot justify airline–HSR cooperation.     

CO2 emissions and expansion of railway,road, airline and in-land waterway networks over the 1985–2013 period in China: A time series analysis

China, the world’s largest CO₂ emitter, is continuing its long-term strategy to use transportation investments as a tool for development. With the expectation that transportation will contribute 30–40% of the total CO₂ emissions in China in the near future, there is an imminent need to identify how the development of different transportation modes may have different long-term effects on CO₂ emissions. Using time series data over the period of 1985–2013, this paper applies the combined autoregressive distributed lag (ARDL) and vector error correction model (VECM) approach to identify short- and long-run causal relationships between CO₂ emissions and mode-specific transportation development, including railway, road, airline, and inland waterway. We find that China’s domestic expansions of road, airline, and waterway infrastructure lead to long-run increases in CO₂ emissions. Among them, waterway has the strongest positive impact on CO₂ emissions, followed by road. Despite a short-run, positive impact on CO₂ emissions, railway expansion leads to long-run decreases in CO₂ emissions. The results are especially encouraging for the central government of China given its long-standing and on-going efforts to expand railway infrastructure at the national level. Looking forward, it is recommended that China continues its national investments in railway infrastructure to achieve both environment and economy goals.     

The environmental cost implication of hub–hub versus hub by-pass flight networks

Increasing congestion at major hubs and the advantage to passengers of non-stop flights and faster journey times has intensified the debate on patterns of air service. At the same time the economics of highly focused networks has been challenged by the availability of very economic smaller capacity long-haul aircraft. The purpose of this research is to value the environmental costs of these two patterns of service: hub-to-hub and hub by-pass. Five long-haul markets were evaluated both on a hub to hub and hub by-pass basis. These involved both transatlantic and Europe/Asia flights. It was found that the noise and emissions social cost impact of the hub by-pass networks was significantly lower than the hub to hub in all cases. Differences in environmental costs per passenger depend on the concentration of population around the airports and the degree to which the hub routing involves extra mileage.     

Modelling the resilience,friability and costs of an air transport network affected by a large-scale disruptive event

This paper deals with developing a methodology for estimating the resilience, friability, and costs of an air transport network affected by a large-scale disruptive event. The network consists of airports and airspace/air routes between them where airlines operate their flights. Resilience is considered as the ability of the network to neutralize the impacts of disruptive event(s). Friability implies reducing the network’s existing resilience due to removing particular nodes/airports and/or links/air routes, and consequently cancelling the affected airline flights. The costs imply additional expenses imposed on airports, airlines, and air passengers as the potentially most affected actors/stakeholders due to mitigating actions such as delaying, cancelling and rerouting particular affected flights. These actions aim at maintaining both the network’s resilience and safety at the acceptable level under given conditions.Large scale disruptive events, which can compromise the resilience and friability of a given air transport network, include bad weather, failures of particular (crucial) network components, the industrial actions of the air transport staff, natural disasters, terrorist threats/attacks and traffic incidents/accidents.The methodology is applied to the selected real-life case under given conditions. In addition, this methodology could be used for pre-selecting the location of airline hub airport(s), assessing the resilience of planned airline schedules and the prospective consequences, and designing mitigating measures before, during, and in the aftermath of a disruptive event. As such, it could, with slight modifications, be applied to transport networks operated by other transport modes.     

Reprint of “Modelling the resilience,friability and costs of an air transport network affected by a large-scale disruptive event”

This paper deals with developing a methodology for estimating the resilience, friability, and costs of an air transport network affected by a large-scale disruptive event. The network consists of airports and airspace/air routes between them where airlines operate their flights. Resilience is considered as the ability of the network to neutralize the impacts of disruptive event(s). Friability implies reducing the network’s existing resilience due to removing particular nodes/airports and/or links/air routes, and consequently cancelling the affected airline flights. The costs imply additional expenses imposed on airports, airlines, and air passengers as the potentially most affected actors/stakeholders due to mitigating actions such as delaying, cancelling and rerouting particular affected flights. These actions aim at maintaining both the network’s resilience and safety at the acceptable level under given conditions.Large scale disruptive events, which can compromise the resilience and friability of a given air transport network, include bad weather, failures of particular (crucial) network components, the industrial actions of the air transport staff, natural disasters, terrorist threats/attacks and traffic incidents/accidents.The methodology is applied to the selected real-life case under given conditions. In addition, this methodology could be used for pre-selecting the location of airline hub airport(s), assessing the resilience of planned airline schedules and the prospective consequences, and designing mitigating measures before, during, and in the aftermath of a disruptive event. As such, it could, with slight modifications, be applied to transport networks operated by other transport modes.     

Combining technology development and behaviour change to meet CO2 cumulative emission budgets for road transport: Case studies for the USA and Europe

Global temperature rise over the long term will be proportional to the total amount of CO₂ emitted. Any given probability of exceeding a targeted maximum temperature rise implies a maximum limit on the cumulative total of CO₂ that can be emitted: a CO₂ “budget”. This paper describes an approach to modelling cumulative emissions from light and heavy duty road transport from the present to 2050, focussing on the USA and Europe, and comparing the potential impacts of a range of technological and behaviourally-based abatement measures with such cumulative emissions budgets.The model shows that abatement measures would have a lower effect on cumulative emissions from 2000 to 2050 than on annual emissions in 2050, so that focussing only on annual emissions could be misleading. It shows that technological developments would be insufficient on their own to enable Europe and the USA to meet CO₂ budgets for road transport. Behavioural changes, which potentially can be implemented much sooner, would be essential too. There is potential to keep European light duty emissions very close to CO₂ budgets, and US light duty emissions not far above the least restrictive budget, but the model predicts that heavy duty emissions in both regions are likely to exceed their CO₂ budgets. Deeper emissions reductions in other regions and sectors will be needed to compensate for this. Timing would be critical: for the greatest impact, behaviour change policies and interventions would need to be applied early and deeply.     

Modeling the relationships among urban passenger travel carbon dioxide emissions,transportation demand and supply,population density,and proxy policy variables

To support the development of policies that reduce greenhouse gas (GHG) emissions by encouraging reduced travel and increased use of efficient transportation modes, it is necessary to better understand the explanatory effects that transportation, population density, and policy variables have on passenger travel related CO₂ emissions. This study presents the development of a model of CO₂ emissions per capita as a function of various explanatory variables using data on 146 urbanized areas in the United States. The model takes into account selectivity bias resulting from the fact that adopting policies aimed at reducing emissions in an urbanized area may be partly driven by the presence of environmental concerns in that area. The results indicate that population density, transit share, freeway lane-miles per capita, private vehicle occupancy, and average travel time have a statistically significant explanatory effect on passenger travel related CO₂ emissions. In addition, the presence of automobile emissions inspection programs, which serves as a proxy indicator of other policies addressing environmental concerns and which could influence travelers in making environmentally favorable travel choices, markedly changes the manner in which transportation variables explain CO₂ emission levels.     

Low-carbon futures for Shenzhen’s urban passenger transport: A human-based approach

Shenzhen, one of China’s leading cities, has the potential to be a model for achieving China’s ambitious CO₂ emission reduction targets. Using data from a travel diary survey in Shenzhen in 2014, we develop a human-based agent model to conduct a scenario study of future urban passenger transport energy consumption and CO₂ emissions from 2014 to 2050. Responses to different policy interventions at the individual level are taken into account. We find that with current policies, the carbon emissions of the urban passenger transport sector in Shenzhen will continuously increase without a peak before 2050. Strengthening 21 transport policies will help Shenzhen to peak the carbon emissions by 2030 for passenger transport. Among these policies, the car quota policy and the fuel economy standard are essential for achieving a carbon peak by 2030. In addition, a package of seven policies, including fewer car quotas, a stricter fuel economy standard, raising parking fees, limiting parking supply, increasing EV charging facilities and subway lines, and improving public transport services, is sufficient to peak carbon emissions by 2030, although at an emissions level higher than for the 21 policies.     

Simulating deep CO2 emission reduction in transport in a general equilibrium framework: The GEM-E3T model

Transport sector restructuring to achieve deep GHG emission cuts has attracted much attention because transportation is important for the economy and inflexible in greenhouse gas emission reduction. The aim of this paper is to simulate transition towards low carbon transportation in the European Union until 2050 and to assess the ensuing macroeconomic and sectorial impacts. Transport restructuring is dynamically simulated using a new transport-oriented version of the computable general equilibrium model GEM-E3 which is linked with the PRIMES-TREMOVE energy and transport sectors model. The analysis draws from comparing a reference scenario projection for the EU member-states up to 2050 to alternative transport policy scenarios and sensitivities which involve deep cutting of CO₂ emissions. The simulations show that transport restructuring affects the economy through multiple channels, including investment in infrastructure, the purchasing and manufacturing of new technology vehicles, the production of alternative fuels, such as biofuels and electricity. The analysis identifies positive impacts of industrial activity and other sectors stemming from these activities. However, the implied costs of freight and passenger transportation are of crucial importance for the net impact on GDP and income. Should the transport sector transformation imply high unit costs of transport services, crowding out effects in the economy can offset the benefits. This implies that the technology and productivity progress assumptions can be decisive for the sign of GDP impacts. A robust conclusion is that the transport sector decarbonisation, is likely to have only small negative impacts on the EU GDP compared to business as usual.     

Factors and scenario analysis of transport carbon dioxide emissions in rapidly-developing cities

To identify key factors of transport CO₂ emissions and determine effective policies for emission reductions in fast-growing cities, this study establishes transport CO₂ emission models, quantifying the influences of polycentricity and satellite cities and re-examining the effects of per capita GDP and metro service. Based on the model results, we forecast future residents’ urban transport CO₂ emissions under several scenarios of different urban and transport policies and new energy technologies. We find nonlinear quadratic growth relationship between commuting CO₂ emissions and per capita GDP, and the elasticities of household and individual commuting CO₂ emission to per capita GDP are 1.90% and 1.45%, respectively. Developing job-housing balanced satellite cities and self-contained polycentric city can greatly decrease emissions from high emitters and can contribute to about 51–82% of the emission reductions by 2050 compared with the scenario of business as usual (BAU). Promotion of electric vehicles, electric public buses, metros, and improvement of traditional energy efficiency contributes to about 48–57% of the emission reductions by 2050 compared with the BAU. When these policies and technologies are combined, about 90% of the emissions could be reduced by 2050 compared with the BAU, and the emissions will be about 1.2–4.9 times of the present. The findings suggest that fostering polycentric urban form and job-housing balanced satellite cities is the key step for future transport CO₂ emission reductions. Metro network promotion, energy efficiency improvement, and new energy type applications can also be effective in emission reductions.     

Probabilistic assessment of aviation CO2 emission targets

Passenger demand for air transportation is expected to continue growing into the future. The increase in operations will undoubtedly lead to an escalation in harmful carbon dioxide emissions, an adverse effect that governing bodies have been striving to mitigate. The International Air Transport Association has set aggressive environmental targets for the global aviation industry. This paper investigates the achievability of those targets in the US using a top-down partial equilibrium model of the aviation system complemented with a previously developed fleet turnover procedure. Three ‘enablers’ are considered: aircraft technologies, operational improvements and sustainable biofuels. To account for sources of uncertainty, Monte Carlo simulations are conducted to run a multitude of scenarios. It was found that the likelihood of meeting all targets is extremely low (0.3%) for the expected demand growth rates in the US. Results show that biofuels have the most impact on system CO₂ emissions, responsible for an average 64% of the total savings by 2050 (with aircraft technologies and operational improvements responsible for 31% and 5%, respectively). However, this impact is associated with high uncertainty and very dependent on both biofuel type and availability.     

The effect of uncertainty on US transport-related GHG emissions and fuel consumption out to 2050

The future of US transport energy requirements and emissions is uncertain. Transport policy research has explored a number of scenarios to better understand the future characteristics of US light-duty vehicles. Deterministic scenario analysis is, however, unable to identify the impact of uncertainty on the future US vehicle fleet emissions and energy use. Variables determining the future fleet emissions and fuel use are inherently uncertain and thus the shortfall in understanding the impact of uncertainty on the future of US transport needs to be addressed. This paper uses a stochastic technology and fleet assessment model to quantify the uncertainties in US vehicle fleet emissions and fuel use for a realistic yet ambitious pathway which results in about a 50% reduction in fleet GHG emissions in 2050. The results show the probability distribution of fleet emissions, fuel use, and energy consumption over time out to 2050. The expected value for the fleet fuel consumption is about 450 and 350 billion litres of gasoline equivalent with standard deviations of 40 and 80 in 2030 and 2050, respectively. The expected value for the fleet GHG emissions is about 1360 and 850 Mt CO₂ equivalent with standard deviation of 130 and 230 in 2030 and 2050 respectively. The parameters that are major contributors to variations in emissions and fuel consumption are also identified and ranked through the uncertainty analysis. It is further shown that these major contributors change over time, and include parameters such as: vehicle scrappage rate, annual growth of vehicle kilometres travelled in the near term, total vehicle sales, fuel economy of the dominant naturally-aspirated spark ignition vehicles, and percentage of gasoline displaced by cellulosic ethanol. The findings in this paper demonstrate the importance of taking uncertainties into consideration when choosing amongst alternative fuel and emissions reduction pathways, in the light of their possible consequences.     

Air transportation in a carbon constrained world: Long-term dynamics of policies and strategies for mitigating the carbon footprint of commercial aviation

With increasing demand for air transportation worldwide and decreasing marginal fuel efficiency improvements, the contribution of aviation to climate change relative to other sectors is projected to increase in the future. As a result, growing public and political pressures are likely to further target air transportation to reduce its greenhouse gas emissions. The key challenges faced by policy makers and air transportation industry stakeholders is to reduce aviation greenhouse gas emissions while sustaining mobility for passengers and time-sensitive cargo as well as meeting future demand for air transportation in developing and emerging countries. This paper examines five generic policies for reducing the emissions of commercial aviation; (1) technological efficiency improvements, (2) operational efficiency improvements, (3) use of alternative fuels, (4) demand shift and (5) carbon pricing (i.e. market-based incentives). In order to evaluate the impacts of these policies on total emissions, air transport mobility, airfares and airline profitability, a system dynamics modeling approach was used. The Global Aviation Industry Dynamics (GAID) model captures the systemic interactions and the delayed feedbacks in the air transportation system and allows scenarios testing through simulations. For this analysis, a set of 34 scenarios with various levels of aggressiveness along the five generic policies were simulated and tested. It was found that no single policy can maintain emissions levels steady while increasing projected demand for air transportation. Simulation results suggest that a combination of the proposed policies does produce results that are close to a “weak” sustainability definition of increasing supply to meet new demand needs while maintaining constant or increasing slightly emissions levels. A combination of policies that includes aggressive levels of technological and operations efficiency improvements, use of biofuels along with moderate levels of carbon pricing and short-haul demand shifts efforts achieves a 140% increase in capacity in 2024 over 2004 while only increasing emissions by 20% over 2004. In addition, airline profitability is moderately impacted (10% reduction) compared to other scenarios where profitability is reduced by over 50% which pose a threat to necessary investments and the implementation of mitigating measures to reduce CO2 emissions. This study has shown that an approach based on a portfolio of mitigating measures and policies spanning across technology and operational improvements, use of biofuels, demand shift and carbon pricing is required to transition the air transportation industry close to an operating point of environmental and mobility sustainability.     

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.