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.     

Nature of influence of out‐of‐vehicle time‐related attributes on transit attractiveness: a random parameters logit model analysis

This paper describes the nature of the impacts of walking distances and waiting time on transit use. The relative trade‐offs of walking and transfer components with other transit service attributes are also discussed. A total of 449 completed stated‐preference interviews were collected; with six observations from each respondent, the total number of observations was 2694. This data set was used to estimate the coefficients in different utility functions using a random parameters logit model. The results demonstrated that walking distances to and from transit stops have important and significant nonlinear negative influences on the attractiveness of transit. Transfer waiting time was also shown to have a significant nonlinear negative impact on transit attractiveness. The random parameters logit model had a better model fit than the standard logit model. Some of the findings obtained here are novel, while others are consistent with previous works. These findings have implications for both theory and practice. Copyright © 2014 John Wiley & Sons, Ltd.     

Making meaningful comparisons between road and rail – substituting average energy consumption data for rail with empirical analysis

Within the transport sector, modal shift towards more efficient and less polluting modes could be a key policy goal to help meet targets to reduce energy consumption and carbon emissions. However, making comparisons between modes is not necessarily straightforward. Average energy and emissions data are often relied upon, particularly for, rail, which may not be applicable to a given context. Some UK train operating companies have recently fitted electricity metres to their trains, from which energy consumption data have been obtained. This has enabled an understanding to be gained of how energy consumption and related emissions are affected by a number of factors, including train and service type. Comparisons are made with existing data for road and rail. It is noted that although more specific data can be useful in informing policy and making some decisions, average data continue to play an important role when considering the overall picture.     

Toll product preferences and implications for alternative payment options and going cashless

There has been a great deal of research on deriving estimates of the value of travel time savings (VTTS) as a way of converting travel time benefits of toll roads relative to free routes into monetary units, the major user benefit in the development of forecasts of traffic and hence revenue streams. By contrast there has been almost no consideration given to identifying the role that various tollroad products play in establishing preferences for toll routes over non-tolled routes. Increasingly tollroads give users the option to pay by cash at a toll booth, by electronic tolling or by a pre- or post-paid debit and credit account system involving vehicle identification. The efficiency gained by electronic tolling for both the users and the operator have resulted in moves in many jurisdictions to eliminate cash collection entirely (or not introduce it when introducing a new tolled road facility), and to introduce a range of pre- and post-payment options. This has been accompanied by a growing move to distance-based charging in some contexts which is more cumbersome to structure with a cash option. This paper investigates current and potential travellers’ preferences for a range of toll products and how much individual’s are willing to pay for very specific toll products. Data from a stated choice experiment is used in a mixed logit model to establish the role that toll products play in the context of offered times and costs of alternative routes, in choosing between alternative ways of paying for the use of tolled routes.

Urban transport in Germany: providing feasible alternatives to the car

With the second highest level of car ownership in the world, and the third highest population density in Europe, Germany has adopted a range of policies to balance the many private benefits of car use with its serious social and environmental problems. In order to ‘tame’ the car, most German cities have implemented a twofold strategy of expanding and improving pedestrian, bicycling and public transport alternatives simultaneously with restricting car use and making it more expensive. That has increased political acceptability since the car‐restrictive measures are not perceived as mere punishment of car drivers. The results of this coordinated urban transport strategy have been impressive. Germany, as a whole, has managed to increase public transport use and to stabilize the car share of modal split. Some cities, of course, have been more successful than others, and this paper examines three of the most successful cities: Münster, Freiburg and Munich. In each of the cities, the percentage of travel by bicycling, walking and public transport has been raised over the past 20 years, while the car's share of modal split has fallen. This article documents the range of policies used to restrict car use, both in Germany as a whole, and in the three case‐study cities in particular. The key to success is found to be mutually reinforcing transport and land‐use policies. It is the combination of a whole set of coordinated policies that explains the dramatic success in changing travel behavior.     

汽车面漆的加速酸蚀研究

为建立新的汽车酸蚀试验方法开展了一系列的研究工作,测试了酸雨的组成和pH值,统计了降雨频率和持续时间、空气和样品温度等大量的环境参数,确认pH值、温度、湿度、紫外光谱、样品的辐照量以及样品的放置角度等关键测试参数。通过对这些环境参数的记录分析,研制出一种仿酸雨溶液和一个加速测试程序,并对一款加速老化试验装置进行了改进,使其能极好地模仿户外的酸蚀结果。     

A randomized controlled trial in travel demand management

Transportation - This paper presents a trial aimed at reducing parking demand at a large urban employer through an informational campaign and monetary incentives. A 6-week randomized controlled...     

Stated preference modelling of intra-household decisions: Can you more easily approximate the preference space?

While the study of choices focuses primarily on the individual decision maker, there is growing interest in the examination of the choices made by groups. Much of the research into the choices of multiple decision makers has revealed that they differ significantly to those of individuals. In this study of household vehicle choice we similarly compare individual choices to group choices and support this finding. Consequently any research into choices that involve groups should acquire data from those groups. In this paper we show how this may be done via an interactive agency choice experiment which makes the individual preferences endogenous to the choice of the group. This method and many like it, however, involve significant time, incentive and administrative costs that often make such studies prohibitive. In this paper we also compare another class of model, minimum information group inference, which is designed to provide an overview of the likely group choice and while not having the specificity of detail as other methods, has the advantage of being much easier and cheaper to implement and is perhaps the only methodology that can be employed when it is not feasible for respondents to interact. We find that this method is a good approximation of group choice, mapping the preference space over which group choice is likely to be located.

     

Dynamic pricing of free-floating carsharing networks with sensitivity to travellers’ attitudes towards risk

Transportation - Free-floating carsharing (FFCS) systems are characterised by volatile fleet distribution as well as customers’ heterogeneous price sensitivity and spatiotemporal flexibility....     

Reducing CO<Subscript>2</Subscript> from cars in the European Union

The European Union (EU) recently adopted CO₂ emissions mandates for new passenger cars, requiring steady reductions to 95 gCO₂/km in 2021. We use a multi-sector computable general equilibrium (CGE) model, which includes a private transportation sector with an empirically-based parameterization of the relationship between income growth and demand for vehicle miles traveled. The model also includes representation of fleet turnover, and opportunities for fuel use and emissions abatement, including representation of electric vehicles. We analyze the impact of the mandates on oil demand, CO₂ emissions, and economic welfare, and compare the results to an emission trading scenario that achieves identical emissions reductions. We find that vehicle emission standards reduce CO₂ emissions from transportation by about 50 MtCO₂ and lower the oil expenditures by about €6 billion, but at a net added cost of €12 billion in 2020. Tightening CO₂ standards further after 2021 would cost the EU economy an additional €24–63 billion in 2025, compared with an emission trading system that achieves the same economy-wide CO₂ reduction. We offer a discussion of the design features for incorporating transport into the emission trading system.