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The energy efficiency of freight transportation is a critical issue in the United States in light of the price volatility
of fuels and America’s dependence upon foreign sources of petroleum. Moreover, energy efficiency is important
to environmental policy. The use of fossil fuels for transportation purposes results in the emission of air pollutants...
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Citations
... In the USA, diesel traction is dominant. Actions aimed at improving energy efficiency may include the technical development of the existing internal combustion engines and the improvement of the technique of driving a combustion traction vehicle [59]. The importance of such activities for railways in Japan is marginal due to the dominant electric traction there [60]. ...
Energy is crucial to economic development, but its production usually has a negative impact on the environment. This ambivalence leads to the need for methods to improve energy efficiency. Transportation is one of the largest global energy consumers. Therefore, improving the energy efficiency of transportation is crucial for sustainable development. The aim of this article is to show the limitations of energy management in railways, resulting from the model of market regulation. The question in this context is whether only technological methods can be used in railways to steer its energy efficiency, as is suggested by the existing research. Critical analysis, desk research and a case study of Polish railway undertaking were used to find an answer to the research question. The discussion of the results shows that the European regulatory system leads to greater complications in the field of energy management than in other global regions, where railways are also important for the economy. Due to these limitations, rail operators use indirect methods to measure energy efficiency. Results indicate that although energy efficiency improvements are being achieved, they are mainly due to organizational measures and not technological ones as could be expected based on previous research.
... Freight trains are known for their locomotive advancements, capable of hauling several tons of goods for several miles with limited fuel consumption. In fact, literature shows that the freight railroad competitiveness advantage is due to, among other factors, the reduction in friction that is created from the wheel assembly contacting the rails, as well as aerodynamics, and engine efficiency advancements [1]. These are the main factors that kept the freight train industry more efficient than trailer trucks. ...
... In the table, the average motor power for the simulation was obtained by multiplying the values listed in Table 4 and Table 6 by two to get the total power consumption per wagon and then by 59 wagons to get the total power consumption for the entire train consist. To calculate the total tons hauled by this train consist, the full load of 143 tons (obtained from reference [1]) for one railcar was multiplied by 59 wagons. Studying the results of Table 8, one can conclude that the optimal operating conditions for a train consist of 59 wagons and one locomotive with all healthy bearings are full load running at speeds ranging from 72 km/h (45 mph) to 97 km/h (60 mph). ...
Based on projected freight truck fuel efficiency, freight railroad and equipment suppliers need to identify, evaluate and implement technologies and/or operating practices to maintain traditional railroad economic competitiveness. The railway industry uses systems that record the total energy efficiency of a train but not energy efficiency or consumption by components. Lowering the energy consumption of certain train components will result in an increase in its overall energy efficiency, which will yield cost benefits for all the stakeholders. One component of interest is the railroad bearing whose power consumption varies depending on several factors that include railcar load, train speed, condition of bearing whether it is healthy or defective, and type of defect. Being able to quantify the bearing power consumption, as a function of the variables mentioned earlier, would make it possible to obtain optimal operating condition ranges that minimize energy consumption and maximize train energy efficiency.
Several theoretical studies were performed to estimate the power consumption within railroad bearings, but those studies lacked experimental validation. For almost a decade now, the University Transportation Center for Railway Safety (UTCRS) at the University of Texas Rio Grande Valley (UTRGV) has been collecting power consumption data for railroad bearings under various loads, speeds, ambient temperatures, and bearing condition. The objective of this ongoing study is to use the experimentally acquired power consumption to come up with a correlation that can be used to quantify the bearing power consumption as a function of load, speed, ambient temperature, and bearing condition. Once obtained, the model can then be used to determine optimal operating practices that maximize the railroad bearing energy efficiency. In addition, the developed model will provide insight into possible areas of improvement for the next generation of energy efficient railroad bearings. This paper will discuss ongoing work including experimental setup and findings of energy consumption of bearings as function of railcar load, train speed, condition of bearing whether it is healthy or defective, and type of defect. Findings of energy consumption are converted into approximations of diesel gallons to quantify the effect of nominal energy consumption of the bearings and show economic value and environmental impact.
... Moreover, fuel consumption can be calculated based on the engine performance (bsfc), and the speed profile which is specific for each operational route 15,16) . This is reported in separate paper (ref; paper under preparation). ...
This paper describes a study on the development of methodology to select the most appropriate technology, and the most optimum design and configuration for the propulsion system of the semi-high speed intercity train that will be operated on the Jakarta-Surabaya corridor. It also describes the method to calculate resistance loads and tractive forces and hence the power required to propel the train along the specified route within targeted time. Among the output of this study is a recommendation for the most optimum propulsion system with basic/ main parameters for main components such as diesel engine, traction motor and the possibility of Diesel Electric Multiple Unit (DEMU) Hybrid battery system.
... People and goods. It is estimated that the exergy destruction of moving goods is 600-800 ton-mile/gallon for railroads, 200-300 ton-mile/gallon for trucks, and 900-1000 ton-mile/gallon for barges (Tolliver et al., 2013) (Table 1). The exergy is destroyed because there is no change in the energy state of the goods moved, merely the location, and the exergy used is not recoverable because it is rejected as heat to the reference environment. ...
Not in my backyard " (NIMBY) is a euphemism for desiring a particular positive outcome from a system that is remotely located such that it has no local negative effect, or a person who exhibits this characteristic. Everyone wants great mobile phone service, for example, but no one wants to look at a mobile phone tower in their backyard. In this paper " exergy destroyed " is applied as a measure of system sustainability to compare NIMBY vs. more " local " system architectures. We analyze transportation of people, goods, and services and show that such transportation is inherently unsustainable because of the exergy destroyed. We use this to show why NIMBY is less sustainable than more localized architectures. We examine dynamic coupling effects on utility generation for NIMBY vs. more local solar electric power architectures and propose an architecture and power distribution method to reduce system costs. We also show that reducing exergy destruction is an inherently lean practice because it reduces waste. Finally, we propose a measure for aligning costs and benefits among different stakeholders as a means to identify more " just " systems.
... The relationship between speed and fuel consumption has been analysed for shipping (Maloni, Paul, & Gligor, 2013), trucking (AEA Technology/Ricardo, 2011), aviation (Delgado & Prats, 2009) and rail (Tolliver, Lu, & Benson, 2013). In the opinion of the World Economic Forum/Accenture (2009) slowing trucks and ships offers the greatest CO 2 abatement potential: ...
The paper challenges the conventional view that the movement of goods through supply chains must continue to accelerate. The compression of freight transit times has been one of the most enduring logistics trends but may not be compatible with governmental climate change policies to cut greenhouse gas emissions by 60–80% by 2050. Opportunities for cutting CO2 emissions by ‘despeeding' are explored within a freight decarbonisation framework and split into three categories: direct, indirect and consequential. Discussion of the direct carbon savings focuses on the trucking and deep-sea container sectors, where there is clear evidence that slower operation cuts cost, energy and emissions and can be accommodated within current supply chain requirements. Indirect emission reductions could accrue from more localised sourcing and a relaxation of just-in-time (JIT) replenishment. Acceleration of logistical activities other than transport could offset increases in freight transit times, allowing the overall carbon intensity of supply chains to reduce with minimal loss of performance. Consequential deceleration results from other decarbonisation initiatives such as freight modal split and a shift to lower carbon fuels. Having reviewed evidence drawn from a broad range of sources, the paper concludes that freight deceleration is a promising decarbonisation option, but raises a number of important issues that will require new empirical research.
... 28 Future technology improvements and system optimization are expected to reduce rail fuel intensity. 39 Several studies predict a fuel intensity reduction of 20%−50% by 2050. 5,37,38 We assumed a 25% linear reduction in the fuel intensity of rail fleet from 2007 to 2050. ...
This work develops an integrated model approach to estimate emissions from long-haul freight truck and rail transport in the U.S. between 2010 and 2050. We connect models of macroeconomic activity, freight demand by commodity, transportation networks, and emission technology to represent different pathways of future freight emissions. Emissions of particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), and total hydrocarbon (THC) decrease by 60%-70% from 2010 to 2030, as older vehicles built to less stringent emission standards retire. Climate policy, in the form of carbon tax that increases apparent fuel prices, causes a shift from truck to rail, resulting in a 30% reduction in fuel consumption and 10%-28% reduction in pollutant emissions by 2050, if rail capacity is sufficient. Eliminating high-emitting conditions in the truck fleet affects air pollutants by 20% to 65%; although these estimates are highly uncertain, they indicate the importance of durability in vehicle engines and emission control systems. Future infrastructure investment will be required both to meet transport demand and to enable actions that reduce emissions of air and climate pollutants. By driving the integrated model framework with two macroeconomic scenarios, we show that the effect of carbon tax on air pollution is robust regardless of growth levels.
The industrial supply chain is a significant consumer of limited energy resources worldwide. Companies have been encouraged to reduce energy costs by restructuring their logistics network, improving their transportation asset fuel efficiency, and reducing travel distance. The recent evolution of synchromodal supply chains has focused on flexible transportation modes as a new option for supply chain managers to reduce the total energy cost. Illustrating the monetary advantages of such reconfigurations will guide decision makers to get the most from all available options.
In this paper, the process of modeling and developing a user-friendly, customizable tool for supply chain decision makers called the Synchromodal Supply Chain Energy Analysis tool (SySCEA) is presented. SySCEA enables the analysis of the overall environmental and economic effects due to supply chain fuel consumption and changing network configuration as it relates to order quantity, demand quantity, product size, packaging, mode and transportation assets. Currently, SySCEA supports up to five arc/routes, plus the first and last mile, for a synchromodal supply chain. However, due to the modular nature of the tool it is simple to extend it to larger networks.
Trains rock and roll around three or more times as fuel efficiently as trucks. Trains use just one gallon to move a ton 476 miles, using just 2 % of U.S. transportation fuel (USDOT 2012).
