• Energy Research
• PL close
• CZ close
• Energies close
• Transport Research close

Car-sharing services are developing at an ever-increasing pace. Taking into account the reduction of carbon dioxide emissions and pursuit of the sustainable development of transport, implementing electric cars in car-sharing fleets is being proposed. On the one hand, these types of vehicles are referred to as emission-free, but on the other hand, their environmental friendliness is questionable due to the emission of carbon dioxide during the production of energy to power them. Although many scientific papers are devoted to the issue of reducing emissions through car sharing, there is a research gap concerning the real production of carbon dioxide by car-sharing vehicles during car-sharing trips. To fill this research gap, the objective of the article was to analyze the actual level of carbon dioxide emissions from combustion and electric vehicles from car-sharing systems produced when renting rides. The test results showed that the electric car turned out to be significantly less emitting. The use of electric vehicles in car-sharing fleets can reduce carbon dioxide emissions from 14% to 65% compared to using cars with internal combustion engines. However, the key role during car-sharing trips is played by the driving style of the drivers, which has been omitted from the literature to date. This should be properly regulated by service providers and focus on the proper use of energy from electric vehicle batteries, especially at low temperatures. The article provides support for operators planning to modernize their fleet of vehicles and fills the research gap concerning car-sharing emissions.

The growing number of electric vehicles in recent years is observable in almost all countries. The country’s energy transition should accompany this rise in electromobility if it is currently generated from non-renewable sources. Only electric vehicles powered by renewable energy sources can be considered zero-emission. Therefore, it is essential to conduct interdisciplinary research on the feasibility of combining energy recovery/generation structures and testing the energy consumption of electric vehicles under real driving conditions. This work presents a comprehensive approach for evaluating the energy consumption of a modern public building–electric vehicle system within a specific location. The original methodology developed includes surveys that demonstrate the required mobility range to be provided to occupants of the building under consideration. In the next step, an energy balance was performed for a novel near-zero energy building equipped with a 199.8 kWp photovoltaic installation, the energy from which can be used to charge an electric vehicle. The analysis considered the variation in vehicle energy consumption by season (winter/summer), the actual charging profile of the vehicle, and the parking periods required to achieve the target range for the user.

Medium and heavy-duty battery electric trucks (BETs) may play a key role in mitigating greenhouse gas (GHG) emissions from road freight transport. However, technological challenges such as limited range and cargo carrying capacity as well as the required charging time need to be efficiently addressed before the large-scale adoption of BETs. In this study, we apply a geospatial data analysis approach by using a battery electric vehicle potential (BEVPO) model with the datasets of road freight transport surveys for analyzing the potential of large-scale BET adoption in Finland and Switzerland for trucks with gross vehicle weight (GVW) of over 3.5 t. Our results show that trucks with payload capacities up to 30 t have the most potential for electrification by relying on the currently available battery and plug-in charging technology, with 93% (55% tkm) and 89% (84% tkm) trip coverage in Finland and Switzerland, respectively. Electric road systems (ERSs) would be essential for covering 51% trips (41% tkm) of heavy-duty trucks heavier than 30 t in Finland. Furthermore, range-extender technology could improve the trip electrification potential by 3–10 percentage points (4–12 percentage points of tkm).

The article pertains to the utilization of the application potential of MCDM/MCDA (Multi-Criteria Decision Making/Multi-Criteria Decision Analysis) methods in decision-making problems in the field of transport in light of sustainable development. The article consists of a theoretical and an empirical part. As part of the literature studies, a review was carried out on the latest applications of MCDM/MCDA methods for decision-making problems in the field of transport. In the empirical part, a multi-criteria analysis of the placement selection for a strip of expressway located in north-eastern Poland was carried out. For this purpose, a hybrid approach was used, consisting of three selected MCDM/MCDA methods: DEMATEL, REMBRANDT, and VIKOR. The ranking was compared with the results achieved in the EIA report of the investment and the results were obtained by using a different set of MCDM/MCDA methods that were proposed in the first part of the research, i.e., AHP, Fuzzy AHP, TOPSIS, and PROMETHEE. The performed multi-criteria analyses allowed for an eventual multi-dimensional evaluation of the most popular MCDM/MCDA methods currently applied in the field of transport.

The growing popularity of traveling with electric scooters in recent years is, on the one hand, a great opportunity to shift from the current forms of mobility to a new service among the public, but it is also a huge challenge for urban centers and operators. One of the main challenges related to electric scooters is the growing demand for high energy consumption, which is currently a big issue due to the growing interest in electromobility used in mobility as a service (MaaS) systems. However, in order to properly estimate the level of energy consumption of scooters, there is a real need for reliable scientific information on the actual electricity consumption of electric scooters used in shared mobility systems. An extensive literature analysis indicates the lack of research conducted in this area. Noting this research gap, studies were conducted to determine the factors influencing the energy consumption of an electric scooter. The study attempts to determine these values on the basis of the proposed research experiment. The scientific experiment was based on a three-factor plan; an experimental plan. The author conducted the research by driving and measuring electric scooters in order to compare the actual consumption with the data provided by vehicle manufacturers. The result of the research was to determine the influence of factors that influence the significant energy consumption of electric scooters from shared mobility systems. Interestingly, the results generated show that the electricity requirements for six scooters corresponded to one electric car. This proposal raises the question of whether scooters are the best form of electric mobility for the environment. In addition, the work also includes guidelines for scooter users and recommendations for shared mobility operators on the energy consumption of electric scooters.

Forests are the main sources of wood chips delivered to the end customers by road or railway. This research analysed the impact of the quarter of the year: Q1 (January–March), Q2 (April–June), Q3 (July–September), Q4 (October–December) when wood chips were obtained over two consecutive years (2019–2020) and the type of transport used (railway and road) on the thermophysical properties of wood chips and the cost of their delivery. The mean moisture content in the wood chips was 38.28% and it was the highest (45.55%) in Q1, while in Q2 and Q3, this parameter was 8 and 17 percentage points (p.p.) lower. The mean lower heating value (LHV) of the chips was 10.46 GJ Mg−1. The chips delivered by road transport had a 4% higher LHV compared to those shipped by railway transport. The wood chips contained 3.42% d.m. of ash. The road transport at a distance of 200 km was found to be approximately 10% cheaper compared to the transport by rail for most of the study period, both with respect to 1 Mg of fresh or dry mass and 1 GJ of energy in the chips. The railway transport was cheaper in the winter (Q1).

Cities have been struggling for many years with many transport problems, including the impact of carbon monoxide emitted by vehicles on the environment, traffic jams, high energy consumption, numerous accidents or high infrastructure costs. There is also a dynamic growth of vehicles on the roads, which is why an increasing number of cities are introducing intelligent transportation systems (ITS), which is part of the concept of smart cities. This paper proposes a new matrix to assess the effects of the ITS implementation in the context of a concept Smart City, which consists of five criteria: (1) movement speed; (2) safety; (3) environmental; (4) economic; (5) satisfaction and amenities for society/passengers. In this new approach the benchmark values of the indicators assigned to the criteria are involved and, therefore, it is possible to determine the level of effectiveness of the ITS in public transport that uses low-carbon energy. This research used literature studies to establish the criteria of effectiveness of ITS as well as a case study, namely public transport that uses low-carbon energy in a Polish city, which had the largest fleet of electric buses in Poland and implements and uses an ITS. Both, the theoretical and the empirical research results demonstrate the usefulness and potency of the proposed matrix to assess the effects of the ITS implementation in cities in the context of the development of a smart city. In that way, the proposed approach may be a useful tool for measuring the effects of ITS implementation in cities.