Traffic Noise in Europe: A Comparison of Calculation Methods,Noise Indices and Noise Standards for Road and Railroad Traffic in Europe

The demand for inland freight transport in Europe is mainly met by road transport, leading to unsustainable impacts such as air pollution, greenhouse gas emissions and congestion. Since rail transport has lower externalities than road transport, a modal shift from road to rail is an accepted policy goal for achieving a more sustainable and competitive transport system. However, intermodal road–rail transport is mainly competitive for long-distance transport, and as a consequence, the potential for modal shift is limited. The cost efficiency of road–rail intermodal transport is particularly sensitive to pre- and post-haulage (PPH) costs, since this activity typically has a larger cost compared with its share of the total distance in the transport chain. For intermodal transportation over shorter distances, for example, below 300 km and where there are substantial PPH activities at both ends of the chain, the competitiveness of the intermodal transport system compared with that of direct road is low. Improving the efficiency of PPH activities is, therefore, of utmost importance for the competitiveness of the intermodal transport system. This paper looks into the issue of improving the cost efficiency of an intermodal transport chain by implementing an innovative and flexible legal framework regarding the PPH activities in the chain. By extending the legal framework with exemptions for longer vehicles in PPH, the cost efficiency could be greatly improved. The purpose of such a framework is to allow and enable, for PPH exclusively, the use of 2?×?40 foot or even two semi-trailers using only one vehicle in the context of the Swedish regulatory framework. This paper develops a strategic calculation model for assessing and investigating the consequences of such a framework and investigates the framework's potential in terms of cost efficiency. The model in combination with a sensitivity analysis of input variables gives a comprehensive understanding of the effects of PPH under different circumstances. From the results, it is evident that there are substantial positive effects associated with a PPH framework of longer vehicles. Results indicate that a typical shipper may experience cost reductions of about 5–10% of the total costs of the intermodal transport chain. In summary, a more innovative and flexible legal framework regarding vehicle length in the PPH links can contribute to a greater modal shift, improved cost efficiency and more environmentally friendly transportation systems.     

Short Sea Shipping’s Green Label at Risk

Abstract

Shifting cargo from land‐based modes to maritime transport has been a prioritized policy in many policy papers to make transport more environmental friendly. Traditional calculations of emissions per transport capacity unit have supported this. However, maritime transport may stand to loose its good environmental reputation in comparison to road transport due to (1) the sluggish processes in maritime environmental policies and the low ambition level of current regulations, (2) the much higher focus on improving the environmental efficiency of the road haulage industry, (3) the much longer economic life of vessels compared to trucks, and (4) focus on faster vessels that increase the average fuel consumption of the sea transport alternative. Through a realistic case study, the energy efficiency and emissions of alternative multimodal transport chains is presented to illustrate these points.     

Assessing greenhouse gas emissions from port vessel operations at the Port of Incheon

This paper measures greenhouse gas emissions from port vessel operations by considering the case of Korea’s Port of Incheon. It provides estimates of greenhouse gas emissions based on the type and the movement of a vessel from the moment of its arrival, to its docking, cargo handling, and departure. Taking a bottom-up approach based on individual vessels’ characteristics and using data on vessels processed by the port in 2012 estimate emissions. The results indicate that the level of emissions is five times higher than that estimated through the top-down approach. Among various types of vessels, international car ferries are the heaviest emitters, followed by full container vessels and car carriers. A vessel’s passage through lock gates and maneuver to approach the dock accounts for 96% of its emissions. Docking for cargo handling shows the lowest level of GHG emissions.     

Achieving transport modal split targets at intermodal freight hubs using a model predictive approach

The increase of international freight commerce is creating pressure on the existing transport network. Cooperation between the different transport parties (e.g., terminal managers, forwarders and transport providers) is required to increase the network throughput using the same infrastructure. The intermodal hubs are locations where cargo is stored and can switch transport modality while approaching the final destination. Decisions regarding cargo assignment are based on cargo properties. Cargo properties can be fixed (e.g., destination, volume, weight) or time varying (remaining time until due time or goods expiration date). The intermodal hub manager, with access to certain cargo information, can promote cooperation with and among different transport providers that pick up and deliver cargo at the hub. In this paper, cargo evolution at intermodal hubs is modeled based on a mass balance, taking into account hub cargo inflows and outflows, plus an update of the remaining time until cargo due time. Using this model, written in a state-space representation, we propose a model predictive approach to address the Modal Split Aware – Cargo Assignment Problem (MSA–CAP). The MSA–CAP concerns the cargo assignment to the available transport capacity such that the final destination can be reached on time while taking into consideration the transport modality used. The model predictive approach can anticipate cargo peaks at the hub and assigns cargo in advance, following a push of cargo towards the final destination approach. Through the addition of a modal split constraint it is possible to guide the daily cargo assignment to achieve a transport modal split target over a defined period of time. Numerical experiments illustrate the validity of these statements.     

Fuel demand,road transport pollution emissions and residents’ health losses in the transitional China

In recent years, China’s rapid economic growth resulted in serious air pollution, which caused substantial losses to economic development and residents’ health. In particular, the road transport sector has been blamed to be one of the major emitters. During the past decades, fluctuation in the international oil prices has imposed significant impacts on the China’s road transport sector. Therefore, inspired by Li and Zhou (2005), we propose an assumption that China’s provincial economies are independent “economic entities”. Based on this assumption, we investigate the China’s road transport fuel (i.e., gasoline and diesel) demand system by using the panel data of all 31 Chinese provinces except Hong Kong, Macau and Taiwan. To connect the fuel demand system and the air pollution emissions, we propose the concept of pollution emissions elasticities to estimate the air pollution emissions from the road transport sector, and residents’ health losses by a simplified approach consisting of air pollution concentrations and health loss assessment models under different scenarios based on real-world oil price fluctuations. Our framework, to the best of our knowledge, is the first attempt to address the transmission mechanism between the fuel demand system in road transport sector and residents’ health losses in the transitional China.     

Greenhouse gas emissions from road transport in South Africa and Lesotho between 2000 and 2009

Road transport is the major source of global greenhouse gas emissions from the transport sector, contributing about three quarters towards the total transport emissions. This study used the Intergovernmental Panel on Climate Change Tier 2 approach to calculate greenhouse gas emissions from road transport in South Africa and Lesotho between 2000 and 2009. Key transport emitting sources, trend analysis and modal intensities were determined for the two countries. For South Africa, provincial road transport emissions were calculated from the number of vehicles by vehicle type and distance travelled. Calculations were at a national level in Lesotho. Road transport carbon dioxide equivalent emissions were estimated at 43.5 million tonnes in South Africa and 0.28 million tonnes in Lesotho in 2009. Motorcars and trucks produced 70.6% of the total road transport emissions in South Africa. Road transport emissions increased by approximately 2.6% per year between 2000 and 2009 in South Africa, while they increased by approximately 2.5% per annum in Lesotho over the same period. Gauteng province had the highest emissions, contributing approximately a third of total road transport emissions in South Africa; while the Northern Cape contributed only 2%. Minibus taxis were the most efficient transport mode on the basis of load carried. The Northern Cape had the highest emissions per passenger-kilometres and tonne-kilometre while the North West had the lowest. Trend assessment showed that emissions from trucks increased rapidly while emissions from other modes of transport decreased over the study period.     

GHG-emission models for assessing the eco-friendliness of road and rail freight transports

Intermodal rail/road transportation is an instrument of green logistics, which may help reducing transport related greenhouse gas (GHG) emissions. In order to assess the environmental impact of road and rail transports, researchers have formulated very detailed microscopic models, which determine vehicle emissions precisely based on a vast number of parameters. They also developed macroscopic models, which estimate emissions more roughly from few parameters that are considered most influential. One of the goals of this paper is to develop mesoscopic models that combine the preciseness of micro-models while requiring only little more information than macro-models. We propose emission models designed for transport planning purposes which are simple to calibrate by transport managers. Despite their compactness, our models are able to reflect the influence of various traffic conditions on a transport’s total emissions. Furthermore, contrasting most papers considering either the road or the rail mode, we provide models on a common basis for both modes of transportation. We validate our models using popular micro- and macroscopic models and we apply them to artificial and real world transport scenarios to identify under which circumstances intermodal transports actually effect lower emissions. We find that travel speed and country-specific energy emission factors influence the eco-friendliness of intermodal transports most severely. Hence, the particular route chosen for a transnational intermodal transport is an important but so far neglected option for eco-friendly transportation.     

Low carbon maritime transport: How speed,size and slenderness amounts to substantial capital energy substitution

Three responses that reduce energy consumption and CO₂ emissions in maritime transport are slower speeds, larger vessels and slender hull designs. We use crude oil carriers as our illustrative example; these represent nearly a quarter of international sea cargo movements. We estimate the potential and costs in these which can all be described as capital substituting for energy and emissions. At different degrees of flexibility and time scales: speed reductions are feasible immediately when there are vessels available, though more capital will be tied up in cargo. Deployment of larger and more slender vessels to a greater extent requires fleet renovation, and also investments in ports and infrastructure. A novel finding in our analysis is that if bunker costs rise as a result of emission costs (fees, quotas), then this may depress speeds and emissions more than if they result from higher oil prices. The reason is that for higher oil prices, more capital tied up in cargo may give cargo owners an interest in speeding up, partly counteracting the impulse from fuel costs that tends to slow vessels down. Emission costs, in contrast, do not raise cargo values.     

Freight Transport Deceleration: Its Possible Contribution to the Decarbonisation of Logistics

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.     

A joint optimization model for liner container cargo assignment problem using state-augmented shipping network framework

This paper proposes a state-augmented shipping (SAS) network framework to integrate various activities in liner container shipping chain, including container loading/unloading, transshipment, dwelling at visited ports, in-transit waiting and in-sea transport process. Based on the SAS network framework, we develop a chance-constrained optimization model for a joint cargo assignment problem. The model attempts to maximize the carrier’s profit by simultaneously determining optimal ship fleet capacity setting, ship route schedules and cargo allocation scheme. With a few disparities from previous studies, we take into account two differentiated container demands: deterministic contracted basis demand received from large manufacturers and uncertain spot demand collected from the spot market. The economies of scale of ship size are incorporated to examine the scaling effect of ship capacity setting in the cargo assignment problem. Meanwhile, the schedule coordination strategy is introduced to measure the in-transit waiting time and resultant storage cost. Through two numerical studies, it is demonstrated that the proposed chance-constrained joint optimization model can characterize the impact of carrier’s risk preference on decisions of the container cargo assignment. Moreover, considering the scaling effect of large ships can alleviate the concern of cargo overload rejection and consequently help carriers make more promising ship deployment schemes.     

Determinants of modal choice in freight transport

In the next few years, exciting developments in the field of freight transport are likely to occur. The Channel Tunnel will be perceived as giving railways much greater distance of operation, compared to the current train ferry to/from Great Britain. The further development of swap-body technology will allow easier modal transfer and the creation, in 1992, of a single market in Europe will transform the pattern of trade. All of these are likely to have significant impacts on modal choice, and hence modal split, in freight transport. Reappraisal by many firms of the modes of transport used is likely but will it result in a net transfer of freight from road to rail and, if so, to what extent? To answer such questions, an accurate and reliable method of predicting modal split is required. Research in the past has concentrated on the development of modal split models based on generalised costs. These fail to explain adequately the prevalence of road freight in the UK. From surveys of freight managers within industry, it is clear that models to date rely too heavily on the economic cost factor and too little on behavioural factors (Jeffs 1985). This paper derives from a recent study of freight transport modal choice from the standpoint of the transport decision-maker within the firm. It attempts to shed light on the actual parameters which should be incorporated into a modal split model. Many variables appear to exert an influence on modal choice decision-making process. However, it is possible to categorise them into six main groups, namely: customer-requirements; product-characteristics; company structure/organisation; government interventions; available transport facilities; and perceptions of the decision-maker him/herself. It is the interactions and inter-relationships between these which ultimately determine freight modal split. This study has shown that the relationship between the outcome of the transport decision process and the values of particular determinants of modal split is not straight-forward, due to the complexity and variety of interactions involved. Perhaps one of the main reasons for researchers' failure hitherto to develop a successful modal-split model has been the preoccupation with techniques that rely on the development of common metric (e.g. generalised cost), which has led to the exclusion of some important explanatory variables along quite different dimensions. Another important issue concerns the appropriate level of aggregation. In order not to reduce the explanatory power of the key variables, it is important to work at a disaggregate level, although this does make substantial demands on data. The use of factor analysis enables both the aggregation of information without loss of behavioural reality and the specification of variables in terms of a common metric. In conclusion, freight transport has usually been examined within too narrow a framework. It must be placed firmly within the context of the total industrial process. The demand for freight transport is directly influenced by the level, composition and geographical distribution of production and consumption activities. Freight flows are complex and so it is highly unlikely that a universal mode-choice model can ever be developed. Future research should, therefore, be directed towards developing partial models in response to specific needs of those involved in decision-taking in the freight sector.     

Bottleneck congestion pricing and modal split: Redistribution of toll revenue

The paper examines the question of the redistribution of toll revenue as seen in a bottleneck congestion model. Our objective is to analyse the impact of this redistribution on total cost and on modal split between railroad and road. Following Tabuchi’s two-mode model (Tabuchi, T., 1993. Bottleneck congestion and modal split. Journal of Urban Economics 34, 414-431.), we integrate a redistribution of toll revenue towards public transport into our study. In this context, we investigate two kinds of road toll regimes: a fine toll and a uniform toll. We will consider two types of railroad fare: when it is set equal to the marginal cost and when it is set equal to average cost. These models allow us to show that toll policy to be more efficient as long as toll revenue is directed towards public transport when the railroad fare is equal to average cost.     

Assessing carbon footprint and energy efficiency in competing supply chains: Review - Case studies and benchmarking

This article compares the energy consumption and CO₂ emissions of supply chains in Belgium, France and UK looking in particular at, jeans, yogurts, apples, tomatoes and furniture. We use a generic methodology that allows comparability across the supply chain of products, supply chains, and countries. Our benchmarking show relatively high emissions for maritime transport and the consumer leg, while logistics activities such as storage and road freight exhibit relatively low emissions. The influences of distance, retail type, area density and consumer behaviour are also examined.     

Road transport and climate change: Stepping off the greenhouse gas

Transport is Australia’s third largest and second fastest growing source of greenhouse gas (GHG) emissions. The road transport sector makes up 88% of total transport emissions and the projected emissions increase from 1990 to 2020 is 64%. Achieving prospective emission reduction targets will pose major challenges for the road transport sector. This paper investigates two targets for reducing Australian road transport greenhouse gas emissions, and what they might mean for the sector: emissions in 2020 being 20% below 2000 levels; and emissions in 2050 being 80% below 2000 levels. Six ways in which emissions might be reduced to achieve these targets are considered. The analysis suggests that major behavioural and technological changes will be required to deliver significant emission reductions, with very substantial reductions in vehicle emission intensity being absolutely vital to making major inroads in road transport GHG emissions.     

Modelling inter-urban transport flows in Italy: A comparison between neural network analysis and logit analysis

In the present paper a modal split problem is analysed by means of two competing statistical models, the traditional logit model and the new technique for information processing, viz. the feedforward neural network model. This study aims to explore the modal split between rail and road transport modes in Italy in relation to the introduction of a new technological innovation, the new High-Speed Train. The paper is sub-divided into two major parts. The first part offers some general considerations on the use of neural networks in the light of the increasing number of empirical applications in the specific area of transport economics. The second part describes the Italian case study by using the two above mentioned statistical models. The results highlights the fact that the two adopted models, although methodologically different, are both able to provide a reasonable spatial forecasting of the phenomenon studied. In particular, the neural network model turns out to have a slightly better performance, even though there are still critical problems inherent in its application.     

Modelling mode choice for freight transport using advanced choice experiments

In this paper we use advanced choice modelling techniques to analyse demand for freight transport in a context of modal choice. To this end, a stated preference (SP) survey was conducted in order to estimate freight shipper preferences for the main attributes that define the service offered by the different transport modes. From a methodological point of view, we focus on two critical issues in the construction of efficient choice experiments. Firstly, in obtaining good quality prior information about the parameters; and secondly, in the improved quality of the experimental data by tailoring a specific efficient design for every respondent in the sample.With these data, different mixed logit models incorporating panel correlation effects and accounting for systematic and random taste heterogeneity are estimated. For the best model specification we obtain the willingness to pay for improving the level of service and the elasticity of the choice probabilities for the different attributes. Our model provide interesting results that can be used to analyse the potential diversion of traffic from road (the current option) to alternative modes, rail or maritime, as well as to help in the obtaining of the modal distribution of commercial traffic between Spain and the European Union, currently passing through the Pyrenees.     

Power unit ‐ Cargo space link in inland waterway navigation

This paper deals with transportation technology regarding links between power unit or motor ship and ship cargo space. These links can be divided into two groups: rigid and flexible. Rigid link, established between power unit and cargo space, is dominant in maritime and road transport (sea ships and trucks), and occasionally in transport on inland waterways (self‐propelled barges). Flexible link is used in railroad transport (between the locomotive and railroad units), partially in road transport (systems with trailers and semitrailers), and in inland waterway transport (push‐towing, pulling systems and combinations of these systems). The main goal of this research is determination of possible link types and organization of fleet for transport on inland waterways in case of flexible link.     

Well-to-wheel assessment of natural gas vehicles and their fuel supply infrastructures – Perspectives on gas in transport in Denmark

In this paper, potential natural gas and renewable natural gas supply pathways and natural gas vehicles (NGVs) have been selected and evaluated with regards to well-to-wheel energy expended, greenhouse gas (GHG) emissions, and regulated (air pollutant) emissions. The vehicles included in the evaluation are passenger cars, light-duty vehicles (LDVs), and heavy-duty vehicles (HDVs) for road-transport applications, and a short-range passenger vessel for maritime transport applications. The results show that, compared to conventional fuels, in both transport applications and for all vehicle classes, the use of compressed and liquefied natural gas has a 15–27% GHG emissions reduction effect per km travel. The effect becomes large, 81–211%, when compressed and liquefied renewable natural gas are used instead. The results are sensitive to the type and source of feedstock used, the type of vehicle engine, assumed methane leakage and methane slip, and the allocated energy and environmental digestate credits, in each pathway. In maritime applications, the use of liquefied natural gas and renewable natural gas instead of low sulfur marine fuels results in a 60–100% SOx and 90–96% PM emissions reduction. A 1% methane slip from a dedicated LNG passenger vessel results, on average, in 8.5% increase in net GHG emissions.     

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.     

Estimation of road transport related air pollution in Saint Petersburg using European and Russian calculation models

The paper analyzes Russian and European emission and dispersion models aimed at the estimation of road transport related air pollution on street and regional scale as exemplified with St. Petersburg, Russia. It demonstrates the results of model calculations of peak concentrations of main harmful substances (NО_X, CO and PM₁₀) along the St. Petersburg Ring Road at high traffic volume and adverse meteorological conditions (calm, temperature inversion) executed by means of a Russian street pollution model, and it evaluates the computed results against the measurements from monitoring stations. The paper also examines the ways of adaptation of the COPERT IV model – a software tool for calculation of air pollutant and greenhouse gas emissions from road transport on regional or country scale – to the inventory conditions of the Russian Federation, compares the COPERT IV numerical estimates with the national inventory data. It also reveals the obstacles and possibilities in the harmonization of the Russian and European approaches.