Improving the energy efficiency of freight in the United States through commodity-based analysis: justification and implementation

Efforts to reduce energy use in freight transportation usually center around “mode-based” approaches, namely improving the energy efficiency of energy intensive modes, such as truck, and shifting more freight to energy efficient modes, such as rail. In the first part of this paper we review the recent trends and future prospects for these mode-based approaches, finding that despite substantial improvement in the technological efficiency of freight modes and robust growth in the use of intermodal rail since 1980, total freight energy use across all modes in the US has grown by approximately 33%, with proportional growth in carbon emissions. In the second part of the paper we propose use of a “commodity-based” approach, in which freight energy use is disaggregated by contribution of major commodity groups, in order to support efficiency improvement at the commodity level. Two potential applications of the commodity based approach, namely (1) life cycle analysis of energy use for major commodity groups and (2) spatial analysis of freight patterns, are demonstrated using the 1993 US Commodity Flow Survey data. Results of these preliminary findings suggest that commodity groups vary widely in the ratio of energy use in production to energy use in transport, and that for many commodity groups, there may be substantial opportunities for saving energy by redistributing flow patterns. Through development of the commodity-based approach, we also identify the collaborative involvement of shippers and carriers as a key point in improving energy efficiency, since it can be used to both make the mode-based approach more effective and address new issues such as the underlying growth in tonne-km. Benefits for air quality and other transportation issues are also discussed.     

Exchange rate and transport cost sensitivities of bilateral freight flows between the US and China

This paper explores the long-run impacts of gross domestic product, exchange rate, and transport costs on bilateral air and ocean freight flows between the US and China. The study employs a cointegration framework by using export and import data over the period of 2003:Q1-2014:Q2. Results show that gross domestic product is the key determinant of bilateral freight flows, indicating that real income of a trading partner is a driving force of the bilateral freight flows between the US and China. In examining the sensitivities of the bilateral trade flows, air freight flows are found to be more responsive to a real income change than ocean freight flows. The bilateral exchange rate is a significant factor affecting the freight flows from China to the US, suggesting that a US dollar appreciation against the Chinese yuan increases the inflows of Chinese commodities to the US. The impacts of the bilateral exchange rate and transport cost are found to vary at industry and commodity levels. These findings support the importance of employing disaggregate data in the bilateral freight flow analysis.     

Origin–destination missing data estimation for freight transportation planning: a gravity model-based regression approach

This paper develops a log-linear regression approach to estimate missing data in a sparse origin–destination (O–D) matrix assuming the sampled or observed O–D trips follow a good gravity pattern. The approach is tested with randomly selected samples from the known portions of 1997, 2002, and 2007 US Commodity Flow Survey (CFS) O–D value and tonnage matrices and validated with 2007 US O–D tonnage matrix at the state level. The missing data are also estimated for the 2007 CFS tonnage matrix with the best intercept and coefficients obtained using all known entries of the matrix. The concept of the approach can be extended beyond the gravity model to any strong mathematical pattern embedded in the known set of a sparse O–D matrix to estimate its missing cells.     

Intermodal and international freight network modeling

The authors describe the development and application of a single, integrated digital representation of a multimodal and transcontinental freight transportation network. The network was constructed to support the simulation of some five million origin to destination freight shipments reported as part of the 1997 United States Commodity Flow Survey. The paper focuses on the routing of the tens of thousands of intermodal freight movements reported in this survey. Routings involve different combinations of truck, rail and water transportation. Geographic information systems (GIS) technology was invaluable in the cost-effective construction and maintenance of this network and in the subsequent validation of mode sequences and route selections. However, computationally efficient routing of intermodal freight shipments was found to be most efficiently accomplished outside the GIS. Selection of appropriate intermodal routes required procedures for linking freight origins and destinations to the transportation network, procedures for modeling intermodal terminal transfers and inter-carrier interlining practices, and a procedure for generating multimodal impedance functions to reflect the relative costs of alternative, survey reported mode sequences.     

Impacts of motor vehicle operation on water quality in the US – Cleanup costs and policies

This paper investigates the costs of controlling some of the environmental impacts of motor vehicle transportation on groundwater and on surface waters. We estimate that annualized costs of cleaning-up leaking underground storage tanks range from $0.8 billion to $2.1 billion per year over 10 years. Annualized costs of controlling highway runoff from principal arterials in the US are much larger: they range from $2.9 billion to $15.6 billion per year over 20 years (1.6–8.3% of annualized highway transportation expenditures). Some causes of non-point source pollution were unintentionally created by regulations or could be addressed by simple design changes of motor vehicles. A review of applicable measures suggests that effective policies should combine economic incentives, information campaigns, and enforcement, coupled with preventive environmental measures. In general, preventing water pollution from motor vehicles would be much cheaper than cleaning it up.     

Lead demand of future vehicle technologies

Changes in battery technology for hybrid or fuel cell vehicles will have significant impacts on US lead flows. Hybrid vehicles contain lead–acid batteries as auxiliary power sources although these lead–acid batteries may be replaced in the future. Given the importance of lead–acid battery recycling to US lead flows, changes in battery-related lead demand could alter the domestic production of lead and affect lead releases to the environment, particularly to air and land. We investigate lead demand for various prospective changes in the US automotive fleet. These include the complete replacement of lead–acid batteries from vehicles (such as next-generation hybrid electric vehicles or use of alternative batteries) or the introduction of micro-hybrid vehicles (lead battery pack vehicles). A dynamic model is described and used to examine the immediate and long-term lead flow patterns, and the associated lead emissions. We conclude that the adoption of non-lead–acid hybrid vehicles does not result in the lead market collapsing unless there is rapid introduction of these vehicles to the fleet, 50% by 2007. A 10% increase in micro-hybrid (battery pack) vehicles results in a predicted increase of 26 tons of lead emissions over the status quo or a 6% increase over 2004 Toxics Release Inventory releases from mining, primary smelting, and secondary smelting.     

Economic analyses of sea-level rise adaptation strategies in transportation considering spatial autocorrelation

This paper reports the impacts of economic analysis results on sea-level rise adaptation decision making with different economic analysis methods. The methodology was applied to Hillsborough County, Florida. A general conclusion is that partial shoreline protection should be implemented to reduce the potential impacts of sea-level rise on important land use, then transportation infrastructure is preferred to be protected or accommodated, and finally managed relocation should be adopted. More specifically, the results show that the best adaptation strategy is shoreline protection plus transportation infrastructure accommodation; the length of shoreline protection plays an important role in the economic analysis results, and shoreline protection and accommodation adaptation strategies for all areas are not recommended because of either high costs or low benefits; the value of travel time saving and spatial autocorrelation play important roles in the economic analysis results of accommodation strategy, which highlights the importance of including indirect economic factors and spatial autocorrelation impacts when making sea-level rise adaptation decisions.     

Impacts of trade related sustainability strategies on freight transportation: Modelling framework and application for France

The circular and functional economies are being presented in the literature as potential strategies for future sustainable societies. In terms of the consequences for supply chains, they will promote a much more dispersed and diversified, local and network based usage of goods than the current economy, which is comparatively linear, concentrated, long distance oriented and scale economy based. A gap in the literature is the assessment of the effects of these systems on freight transport flows. In our paper, we present a first attempt at estimating this impact using freight transport scenario building and quantitative modelling. In order to translate the main parameters that characterize these systems into factors determining freight transportation volumes, we develop a framework based on a typology of goods categories describing functional and spatial proximity between producers and consumers. In order to simulate changes in the economy, we develop scenarios for the shifting of goods from one category to another and, additionally, include internalization policies that should guide their realization. We calculate the impacts on freight flows using a new interregional transport model for France that includes distribution chains and produces estimates of external costs of transport. Our results show that circular and functional economies could lead to a 2–5% reduction of air pollutant emissions and up to a 14–26% reduction if combined with the internalization of external costs. The scenario with ongoing mass production for differentiated demand is found to lead to a 5% increase of environmental impacts compared to the baseline.     

Assessing the energy and greenhouse gas emissions mitigation effectiveness of potential US modal freight policies

This paper estimates the total embodied energy and emissions modal freight requirements across the supply chain for each of over 400 sectors using Bureau of Transportation Statistics Commodity Flow Survey data and Bureau of Economic Analysis economic input-output tables for 2002. Across all sectors, direct domestic truck and rail transportation are similar in magnitude for embodied freight transportation of goods and services in terms of ton-km. However, the sectors differ significantly in energy consumption, greenhouse gas emissions, and costs per ton-km. Recent pressure to reduce energy consumption and emissions has motivated a search for more efficient freight mode choices. One solution would be to shift freight transportation away from modes that require more energy and emit more (e.g., truck) to modes that consume and emit less (e.g., rail and water).Our results show there are no individual sectors for which targeting changes would significantly decrease the total freight transportation energy and emissions, therefore we have also looked at the prospect of policies encouraging many sectors to shift modes. There are four scenarios analyzed: (1) shifting all truck to rail, shifting top 20% sector mode choice, (2) based on their emissions, (3) based on a multi-attribute analysis, and (4) increasing truck efficiency (e.g., mpg). Increasing truck efficiency by 10% results in similar energy and emissions reductions (approximately 7% for energy and 6% for emissions) as targeting the top 20% of sectors when selected based on emissions, whereas selecting the top 20% based on availability to shift from truck results in slightly less reductions of energy and emissions. Implementing policies to encourage higher efficiency in freight trucks may be a sufficient short term goal while efforts to reduce truck freight transportation through sectoral policies are implemented in the long term.     

A modelling system to simulate goods movements at an urban scale

The paper reports a modelling system to simulate goods movements at an urban scale. It allows joint analysis of choices made by end-consumers (assumed to be families) and retailers. These movements are examined at two levels: analysis of commodity flows, in terms of quantity, generated by the consumption of commodities; analysis of commodity flows, in terms of vehicles, due to restocking. The first level allows us to calculate the goods quantity flows due to consumption and restocking; the second level allows us to determine the service, vehicles used and target time, as well as the route chosen for restocking sales outlets in order to estimate vehicle flows on the urban/metropolitan transportation network. The modelling system is a multi-step model and considers a disaggregated approach for each decisional level.     

A study of interstate motor carrier vehicle miles of travel

This article summarizes the evaluation results of six data sources in terms of their ability to estimate the number of commercial trucks operating in interstate commerce and their vehicle miles of travel by carrier type and by state. The six data sources were: (a) Truck Inventory and Use Survey of the U.S. Bureau of the Census; (b) Nationwide Truck Activity and Commodity Survey of the U.S. Bureau of the Census; (c) National Truck Trip Information Survey of the University of Michigan Transportation Research Institute; (d) Highway Performance Monitoring System of the Federal Highway Administration, U.S. Department of Transportation; (e) International Registration Plan of the American Association of Motor Vehicle Administrators; and (f) State fuel tax reports from each individual state and the International Fuel Tax Agreement. Evaluation results concluded that none of the data sources by themselves were capable of providing reliable estimates at the state level. Although several attempts were made to combine the strengths of different data sources so that reliable estimates could be generated, none of them were successful. Data inconsistency and incompatibility contributed primarily to the failures. Although several of the six data sources by themselves could provide estimates at the national level, each had limitations. As a result of these findings, two cost-effective methodologies were proposed to estimate the number of commercial trucks operating in interstate commerce and their vehicle miles of travel by carrier type. Neither method required collecting additional data.     

An activity-based assessment of the potential impacts of plug-in hybrid electric vehicles on energy and emissions using 1-day travel data

This paper assesses the potential energy profile impacts of plug-in hybrid electric vehicles and estimates gasoline and electricity demand impacts for California of their adoption. The results are based on simulations replicating vehicle usage patterns reported in 1-day activity and travel diaries based on the 2000–2001 California Statewide Household Travel Survey. Four charging scenarios are examined. We find that circuit upgrades to 240 V not only bring faster charging times but also reduce charging time differences between PHEV20 and PHEV60; home charging can potentially service 40–50% of travel distances with electric power for PHEV20 and 70–80% for PHEV60; equipping public parking spaces with charging facilities, can potentially convert 60–70% of mileage from fuel to electricity for PHEV20, and 80–90% for PHEV60; and afternoons are found to be exposed to a higher level of emissions.     

Multi-commodity traffic assignment by continuum approximation of network flow with variable demand

Consider a city with several highly compact central business districts (CBD), and the commuters’ destinations from each of them are dispersed over the whole city. Since at a particular location inside the city the traffic movements from different CBDs share the same space and do not cancel out each other as in conventional fluid flow problems albeit travelling in different directions, the traffic flows from a CBD to the destinations over the city are considered as one commodity. The interaction of the traffic flows among different commodities is governed by a cost–flow relationship. The case of variable demand is considered. The primal formulation of the continuum equilibrium model is given and proved to satisfy the user optimal conditions, and the dual formulation of the problem and its complementary conditions are also discussed. A finite element method is then employed to solve the continuum problem. A numerical example is given to illustrate the effectiveness of the proposed method.     

Origin–destination synthesis for aviation network data: examining hub operations in the domestic and international US markets

Hub‐and‐spoke networking is a key feature of current aviation markets in which hubs, as connecting points, function to consolidate and redistribute flows. This indicates that observation of traffic on a segment does not necessarily convey information about the origin to destination routing of passenger journeys because of the unavoidable detours in the system. This paper examines the heterogeneity of the flow composition in domestic and international US markets, which in turn allows us to observe the variation of operations across major hubs. A modified Route Flow Estimator for origin–destination synthesis (or origin–destination matrix estimation) is designed to decompose the segment traffic into itinerary‐based passenger trips. Several public and commercial databases, which are easily accessible, are exploited (and reconciled) for the model in order to (i) generate possible trip itineraries using those segment markets, and (ii) link data‐driven operational conditions with the underlying segment flows. The results are validated with US domestic trip observations and empirical knowledge related to the air transportation system. Then, the variability of the hub operations is examined based on sensitivity tests using the model parameters. From the resolution of itinerary‐based estimates, we observe that major airports' hub operations are spatially uneven, particularly with respect to domestic and international connecting passengers. Copyright © 2017 John Wiley & Sons, Ltd.     

TransNIEMO: economic impact analysis using a model of consistent inter-regional economic and network equilibria

We describe a model that integrates a multiregional input–output (I–O) model of the USA (for 50 States and the District of Columbia) with the national highway network. Inter-state commodity shipments are placed on a congestible highway network. Simulations of major choke-point disruptions redirect traffic which increases the costs of some shipments. Increased costs show up in higher prices which help to determine a new I–O equilibrium. We find economic and network equilibria that are consistent. The simulations show only moderate economic impacts. We ascribe this to the resilience of the highway network. The model provides State-level detail on who bears the costs of the disruptions.     

Impact assessment of extreme weather events on transport networks: A data-driven approach

The present paper presents a data-driven method for assessing the resilience of the European passenger transport network during extreme weather events. The method aims to fill in the gap of current research efforts regarding the quantification of impacts attributed to climate change and the identification of substitutability opportunities between transport modes in case of extreme weather events (EWE). The proposed method consists of three steps concerning the probability estimation of an EWE occurring within a transportation network, the assessment of its impacts and the passengers’ flow shift between various transport modes. A mathematical formulation for the proposed data-driven method is provided and applied in an indicative European small-scale network, in order to assess the impacts of EWE on modal choice. Results are expressed in passenger differentiated flows and the paper concludes with future research steps and directions.     

The asymmetric effects of income and fuel price on air transport demand

Forecasts of passenger demand are an important parameter for aviation planners. Air transport demand models typically assume a perfectly reversible impact of the demand drivers. However, there are reasons to believe that the impacts of some of the demand drivers such as fuel price or income on air transport demand may not be perfectly reversible. Two types of imperfect reversibility, namely asymmetry and hysteresis, are possible. Asymmetry refers to the differences in the demand impacts of a rising price or income from that of a falling price or income. Hysteresis refers to the dependence of the impacts of changing price or income on previous history, especially on previous maximum price or income. We use US time series data and decompose each of fuel price and income into three component series to develop an econometric model for air transport demand that is capable of capturing the potential imperfectly reversible relationships and test for the presence or absence of reversibility. We find statistical evidence of asymmetry and hysteresis – for both, prices and income – in air transport demand. Implications for policy and practice are then discussed.     

Telecommunications and travel demand and supply: Aggregate structural equation models for the US

Disaggregate studies of the impacts of telecommunications applications (e.g. telecommuting) on travel have generally found a net substitution effect. However, such studies have all been short-term and small-scale, and there is reason to believe that when more indirect and longer-term effects are accounted for, complementarity is the likely outcome. At least two aggregate studies have focused on the relationships between telecommunications and travel from economic perspectives (consumer and industry). However, both use the monetary value of consumption or transactions rather than actual activity measures (e.g. miles, number of calls), and neither fully explains the direct and indirect causal relationships between the two. The purpose of this study is to develop a conceptual model in a comprehensive framework, considering causal relationships among travel, telecommunications, land use, economic activity, and socio-demographics, and to explore the aggregate relationships between telecommunications and travel, using structural equation modeling of national time series data spanning 1950–2000 in the US. In this paper we focus on number of telephone calls as the measure of telecommunications, and passenger vehicle–miles traveled as the measure of transportation. Future research will investigate additional measures of these two constructs. Our empirical results strongly support the hypothesis that telecommunications and travel are complementary. That is, as telecommunications demand increases, travel demand increases, and vice versa. These results offer a more realistic picture to policy makers and transportation planners than has been available till now, and suggest useful directions for them to develop transportation or telecommunications strategies designed to reduce traffic congestion, air pollution, and energy consumption.     

Spatiotemporal evolution of China’s railway network in the 20th century: An accessibility approach

The interrelatedness of transportation development and economic growth has been a constant theme of geographic inquiries, particularly in economic and transportation geography. This paper analyzes the expansion of China’s railway network, the evolution of its spatial accessibility, and the impacts on economic growth and urban systems over a time span of about one century (1906–2000). First, major historical events and policies and their effects on railway development in China are reviewed and grouped into four major eras: preliminary construction, network skeleton, corridor building, and deep intensification. All four eras followed a path of “inland expansion.” Second, spatial distribution of accessibility and its evolution are analyzed. The spatial structure of China’s railway network is characterized by “concentric rings” with its major axis in North China and the most accessible city gradually migrating from Tianjin to Zhengzhou. Finally, the study indicates that railway network expansion has significantly improved economic development and heavily influenced the formation of urban systems in China.     

Wildlife strike cost revelation in the US domestic airline industry

Since the Federal Aviation Administration (FAA) last revisited its wildlife strike disclosure policy in 2009, the American domestic airline industry has undergone a significant increase in concentration. We analyze how the aforementioned shift in market structure has impacted the voluntary repair cost disclosure of US airlines following a damaging wildlife strike event. We also investigate the related relationship between profitability and disclosure using an instrumental variables strategy. Lastly, we examine the interaction between competition and profits. Our results show the probability of large American airlines disclosing direct repair costs after a wildlife strike event are linked to market competition and profitability. These findings could directly inform policies managing the economic burden of wildlife strikes, most importantly, the current voluntary disclosure policy.