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Indicators of sustainability and environmental performance can be useful for comparing modes, discerning trends, and formulating appropriate policies. This paper considers the performance of U.S. transportation service sectors through use of 1992 and 1997 benchmark input–output models. Use of these models permits assessment of not only the direct performance of the sectors but also the supply chain impacts required for operation of the transportation sectors. Consideration of indirect impacts is critical for assessment of the overall costs and impacts of particular products or services. Six transportation service sectors (air, rail, water, truck, transit, and pipeline) are examined. Economic impact, energy, greenhouse gas emissions, and toxic emissions are examined. The transportation sectors use large amounts of energy, both in total and per dollar of output and on a per service basis. Pipeline and water transportation have particularly large energy requirements per dollar of output, likely reflecting higher energy intensity and lower labor intensity in these modes. Truck transportation is the most energy intensive of the freight transportation modes per ton-mile of service, but it has a trend toward greater energy efficiency. For greenhouse gas emissions, truck, water, and air transportation have the highest emissions per dollar of output. Water transportation freight rates are sufficiently low that emissions on a per ton-mile basis would be correspondingly low. Finally, the supply chain (indirect) toxic emissions per dollar of output are highest for rail and pipeline transportation. There is considerable work to be done to improve the overall sustainability of the different transportation modes.

In this study, a mixed integer linear programming model that integrates multimodal transport—truck and rail—into the switchgrass-based bioethanol supply chain was formulated. The objective of this study was to minimize the total cost for cultivation and harvesting, infrastructure, the storage process, bioethanol production, and transportation. Strategic decisions, including the number and location of intermodal facilities and biorefineries, and tactical decisions, such as the amount of biomass shipped, processed, and converted into bioethanol, were validated by using North Dakota as a case study. It was found that the multimodal transport scenario was more cost effective than a single mode of transport (truck) and resulted in a lower cost for bioethanol. A sensitivity analysis was conducted to demonstrate the impact of key factors in the decision to use multimodal transport in a switchgrass-based bioethanol supply chain and on the cost of bioethanol.

This paper uses the recently published 2002 Vehicle Inventory and Use survey to determine the number of commercial trucks in the categories that are most likely to idle for periods of more than 0.5 h at a time. On the basis of estimated numbers of hours for both overnight idling by sleepers and long-duration idling by all size classes during their workdays, the total fuel use by idling trucks is estimated to be more than 2 billion gallons per year. Workday idling is determined to be a potentially much larger energy user than overnight idling, but data are required before any definitive conclusions can be reached. Existing technologies can reduce overnight idling, but development may be needed to reduce workday idling.

Abstract We apply an approach that theoretically connects processes at different scales within a sociotechnical sustainability transitions frame, focusing on individual actors. Drawing on interviews with actors involved in the electric mobility transition in Lower Saxony, Germany, we analyse actors’ narratives as revelatory of situated or ‘conjunctural’ knowledge, as viewed from a strong structuration perspective of sociotechnical change. The purpose is to shed a particular type of light on structure-agency processes. Strong structuration is an extended version of Giddens’ social theory that takes account of actors’ subjective experience of their situation, viewing this as both shaped by - and shaping of - structure, in the sense of rules that are internal and external to individuals. Here we show how actors’ narratives of their experiences and positions in the sociotechnical system reveal themes relevant to the on-going structuration electric vehicles in the case study region of Lower Saxony, Germany. We identify general ‘meta-narratives’ that span more than one individual, as well as personal narratives that are specific to individuals. In addition, the analytic value of narratives in transition literature is discussed.

This research into the integrity of glazing is spurred by recent accidents, including the commuter train derailment in Spuyten Duyvil, New York, on December 1, 2013. Four passengers were fatally injured in that accident. All four fatalities were attributed to ejection through window openings. Results of the accident investigation indicate that the rubber gaskets holding the window panes in place pulled out when the cars slid on their sides after leaving the track. The windows were pushed inside the cars and created openings that allowed occupants to be ejected. After its investigation, the National Transportation Safety Board issued a recommendation for more-effective passenger containment by glazing systems in derailments. In addition to functioning as windows, glazing systems are also expected to be impact resistant, to provide emergency egress and emergency access, to be fire resistant, and to provide occupant containment. Research activities include assessing the performance of current glazing systems in meeting all expectations, especially occupant containment, developing modifications for improving safety performance, and comparing the performance of conventional and modified glazing systems. The objective of the Federal Railroad Administration’s (FRA’s) research into the integrity of glazing is to describe comprehensively all the engineering requirements placed on glazing systems and to develop effective strategies for balancing all the safety demands. The integrity of glazing is one of many research topics on the crashworthiness of rail equipment and is conducted by FRA in coordination with other topics, such as the integrity of the side structures of passenger equipment and the protection of occupants.

Electric vehicles offer the potential of climate-friendly driving and have received more and more attention in diffusion research recently. However, the effect of the availability of home charging options on the market potential of electric vehicles has not been targeted in detail in the diffusion process so far, although it represents a beneficial differentiation to conventional vehicles. Therefore, we present an agent-based simulation to address the buying behavior of German consumers regarding electric and plug-in hybrid electric vehicles using empirical data primarily derived from a choice-based conjoint study. We explicitly consider individual possibilities of home charging in our model, which appears to have an important influence on the diffusion of both, electric and plug-in hybrid electric vehicles. However, its importance decreases with faster charging times at public charging stations. Furthermore, our findings reveal that in the longer term, technological progress in charging time, range, and charging station density of electric vehicles is presumably cannibalizing plug-in hybrid electric vehicles’ market shares more than that of conventional vehicles. However, with still lower technological capabilities of electric vehicles, a governmental subsidy can initially promote plug-in hybrid electric vehicles, but electric vehicles will benefit later from that promotional effect.

Users charging the batteries of their electric vehicles in an uncoordinated manner can present energy systems with a challenge. One possible solution, smart charging, relies on the flexibility within each charging process and controls the charging process to optimize different objectives. Effective smart charging requires forecasts of energy requirements and parking duration at the charging station for each individual charging process. We use data from travel logs to create quantile forecasts of parking duration and energy requirements, approximated by upcoming trip distance. For this task, we apply quantile regression, multi-layer perceptrons with tilted loss function, and multivariate conditional kernel density estimators. The out-of-sample evaluation shows that the use of local information from the vehicle's travel data improves the forecasting accuracy by 13.7% for parking duration and 0.56% for trip distance compared to the data generated at the charging stations. In addition, the analysis of a case study shows that using probabilistic forecasts can control the interruption of charging processes more efficiently compared to point forecasts. Probabilistic forecasting leads up to 7.0% less interruptions, which can cause a restriction in drivers' mobility demand. The results show that charging station operators benefit from leveraging the driving patterns of electric vehicles. Thereby, smart charging and the application of the proposed models as benchmarks models for the related forecasting tasks is an improvement for the operators.

Many cities in the United States are facing challenges associated with antiquated urban arterials, whose purpose has changed greatly since their development. Once considered the main streets of the city, with thriving businesses and attractive residential development, many have deteriorated over the decades for a number of reasons, including shifting demand for housing and retail development and the construction of parallel high-speed urban expressways. Because of the complexity of the problems associated with these arterials, a great challenge of transportation and land use planners is to develop a systems-level approach to revitalize and reinvent these arterials in a manner that encourages environmental, economic, and social sustainability. Presented is a methodology to revitalize multimodal urban arterials that includes land use planning, traffic and transit operations management, street redesign, and community participation to improve the conditions of such arterials. Analysis is carried out by using these principles on San Pablo Avenue, a major arterial in the San Francisco Bay Area in California. By using these analysis techniques, land use and transportation recommendations are made that will facilitate sustainable development along this corridor.

Lower Manhattan (LM) is America's fourth-largest central business district and one of the oldest and densest areas in New York City. It is also New York City's fastest-growing residential neighborhood and contains some of the highest levels of pedestrian, transit, and vehicular activity in America. Since September 11, 2001, redevelopment has dramatically transformed the area into a vibrant 24/7 live–work–visit community. The changes present an unprecedented opportunity to create a more livable and environmentally sustainable neighborhood by reducing traffic and managing parking while giving residents and employees better, greener mobility options. Consequently, the city is focused on finding new ways to manage competing demands for different uses of limited street space. Improving street management is paramount to improving the quality of public space and speeding LM's revitalization. In 2004, the Lower Manhattan Development Corporation funded the New York City Economic Development Corporation and the New York City Department of Transportation to contract Arup to undertake a multi-year comprehensive planning study to consider ways to reduce traffic congestion, manage placard parking, and create complete streets and engaging public spaces in LM. This paper discusses the necessity for and development of a proposed street management framework to help guide the city in meeting the transportation and public realm needs of LM's residents, employees, tourists, and businesses. As of October 2008, the project is ongoing; the proposed framework is still conceptual and has not yet been implemented.