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The concept of sustainable transportation of goods as the primary paradigm for designing contemporary logistics systems assumes the use of energy-efficient and affordable modes of transport in a way that guarantees the most cost-efficient variant of the delivery scheme. That especially applies to road transport deliveries, where the number of alternatives for organizing the transportation process is numerous and the choice of the optimal solution is complicated by the multiple stochastic influences of the environment on the technological processes. In this paper, we contribute to solving the problem of shaping the sustainable delivery schemes by proposing an approach to shape the complete set of alternative transport and technological schemes for packaged cargo delivery by road transport. The developed mathematical model allows estimating the efficiency of each alternative delivery scheme for the given request and chooses the best variant that minimizes the total costs of all participants in the delivery process. The proposed algorithms are implemented in the C# programming language within the frame of a class library for modeling transport delivery processes. A case of transport processes for Delivery Ltd. (Kharkiv, Ukraine) is applied to illustrate the procedure of using the developed approach to choose the optimal transport and technological schemes for long-distance deliveries. As the result of simulating the goods transportation processes, we show the regression models that represent dependencies of the total costs for the implementation of a delivery scheme from the parameters of demand for the transportation of goods. These regression models allow estimating the most efficient delivery schemes based on the functional analysis of the obtained dependencies for the given demand parameters.

Abstract An experimental and theoretical investigation is being performed to evaluate exhaust emissions and fuel consumption of Heavy Duty Vehicles (HDVs) circulating in urban areas and involved in commercial shipping activities. The study is focused on the city of Genoa, whose urban road network is influenced by highway connections and shipping activities, as seven motorway exits and more than twenty accesses to port area are located within the urban area. In a first step, the HDV flows crossing highway exits, urban zones and port areas were evaluated, as well as the relevant vehicle classes. The typical urban trips linking highway exits to port gates and the HDV mission profiles within the port area were then defined, whose validation was performed through an experimental campaign for HDV instantaneous speed measurements on urban trips and in port zones. The availability of speed patterns enabled the application of Passenger Car and Heavy Duty Emission Model (PHEM) for the estimation of fuel consumption and emission factors for selected HDV classes. The main results of the different investigation steps are presented and discussed in the paper, outlining the specific activities of HDVs in port area and the relevant emissive behaviour.

The need to mitigate CO2 emissions from the transportation sector has necessitated the adoption of electric vehicles (EVs) and other forms of alternative vehicles. Despite the global rise of EVs demand as a complementary means of green transportations, the level of adoption in Malaysia is still not encouraging. Therefore, this study aimed to investigate the cost competitiveness of EVs in comparison with Hybrid Electric Vehicles (HEVs) and an Internal Combustion Vehicle (ICV) based on Malaysia scenarios. Using the existing data in Malaysia, life cost analysis (LCC) of two EVs was computed and compared with HEVs and ICVs. The study shows that Nissan leaf and BMW i3s EVs with LCC of $1.75 and $2.5 per km are not cost-competitive based on prevalent data available in Malaysia compared to the HEVs and ICV. Based on the sensitivity analysis, changes in the components of the operating costs significantly influence the accumulated cost of ownership of the EVs whereas the cost of ownership of the HEVs and ICVs did not experience any significant influence. The findings from this study could serve as bases for policymakers to formulate appropriate policies and strategies to improve the competitiveness of EVs in Malaysia.

The transport system causes extremely harmful consequences for society and the environment. It is manifested through the increased emission of harmful exhaust gases, traffic congestions, traffic accidents, increased level of noise, higher levels of stress and various diseases of all participants of the transport system and society in general. The implementation and modernization of intermodality through the Motorways of the Sea (MoS) as its ecological and socio-economic sustainable subsystem is the efficient way of reducing the above mentioned consequences. Further sustainable development of MoS can be observed according to the ecological and socio-economic criteria and sub-criteria set out in this paper in order to keep it in direct function of protecting the society and preserving the environment.

According to the Canarian government’s plans, a complete decarbonization of the Canary Islands economy is foreseen from 2040 onwards, which includes the electrification of land transport in the archipelago. However, due to the current low penetration rate of electric vehicles (EVs) on the islands, the number of EVs in circulation is expected to grow significantly in the coming years. Despite this, the network of charging points in Tenerife is currently totally insufficient, which is why it is essential to carry out a study to design the network of charging points in such a way that it can absorb the entire fleet of EVs that is expected to be in place by 2040. To this end, there are studies on the capacity, in terms of parking space, available for the installation of these charging points, but to date there are no studies on this subject supported by mobility data. For this reason, a simulation of traffic in Tenerife in 2040 has been carried out using MATSim (Multi-Agent Transport Simulation) to determine the ideal places to install these charging points and to find the number of charging points needed for the network.

The annual reporting procedures of the United Nations Framework Convention on Climate Change (UNFCCC) have now produced greenhouse gas (GHG) emission inventories from 40 so-called Annex I countries for 18 years. This article analyses a subset of these data: emissions from road transport. The article compares the reported data with the technical guidance on GHG emission inventories provided by the Intergovernmental Panel on Climate Change (IPCC). The analysis suggests that some countries use the IPCC's default emission factors, whereas other countries use country-specific values. In the case of diesel-fuelled road transport, the estimated emissions appear to be generally comparable between all countries for all years. For CO2 emissions from gasoline-fuelled road transport, the picture is less clear. The results suggest that the default emission factor for CO2 from motor gasoline as provided by the IPCC is about 3-5% too low. Countries that seem to apply this default value might therefore underestimate their emissions by the same percentage. The effect of this possible underestimate on trends is, however, very small. Despite the possible problem with the default emission factor, the quantification of the trend in emissions is only slightly influenced by this. © 2011 Earthscan.