Search Results (97)

The Middle East and North Africa region has not played a major role in climate action so far, and several countries depend economically on fossil fuel exports. However, this is a region with vast solar energy resources, which can be exploited affordably for power generation and hydrogen production at scale to eventually reach carbon neutrality. In this paper, we elaborate on the case of the United Arab Emirates and explore the aspirations and feasibility of its net-zero by 2050 target. While we affirm the concept per se, we also highlight the technological complexity and economic dimensions that accompany such transformation. We expect the UAE’s electricity demand to triple between today and 2050, and the annual green hydrogen production is expected to reach 3.5 Mt, accounting for over 40% of the electricity consumption. Green hydrogen will provide power-to-fuel solutions for aviation, maritime transport and hard-to-abate industries. At the same time, electrification will intensify—most importantly in road transport and low-temperature heat demands. The UAE can meet its future electricity demands primarily with solar power, followed by natural gas power plants with carbon capture, utilization and storage, while the role of nuclear power in the long term is unclear at this stage. Full article

Currently, the market for cars based on alternative fuels is developing very dynamically, which is caused by the growing needs in the field of environmental protection and the desire to reduce dependence on fossil fuels. Many countries have introduced various forms of support for people who decide to buy an electric or a hybrid car. The European Union has also introduced increasingly restrictive CO₂ emission standards, which accelerates the transition to alternative drives. The main research question in the paper was how the market for alternative energy sources in transport is developing in individual countries of the community, what the infrastructure looks like, and whether there is a large diversity in this field in the countries under study. The taxonomic methods (the TOPSIS method and the cluster analysis) have been applied for the research. The data were taken from Eurostat and the European Alternative Fuels Observatory statistical data. The analysis allowed an identification of key regularities that characterize the process of transformation of road transport in the European Union. Firstly, there is a clear division in countries with a high level of electrification (clusters I, IV, and VI) and countries that prefer gas drives (cluster V) or that are at an early stage of transformation (clusters II and III). Secondly, a strong relationship between the development of charging infrastructure, especially ultra-fast stations, and the level of adoption of electric vehicles was confirmed. Full article

Urban population growth is intensifying pressure on mobility systems, with road transportation contributing to environmental and sustainability challenges. Policymakers must navigate complex uncertainties in addressing rising mobility demand while pursuing sustainability goals. Advanced technologies offer promise, but their real-world effectiveness in urban contexts remains underexplored. This meta-review comprised three complementary studies: a broad analysis of sustainable mobility with Norwegian case studies, and systematic literature reviews on digital twins and Big Data/AI applications in urban mobility, covering the period of 2019–2024. Using structured criteria, we synthesised findings from 72 relevant articles to identify major trends, limitations, and opportunities. The findings show that mobility policies often prioritise technocentric solutions that unintentionally hinder sustainability goals. Digital twins show potential for traffic simulation, urban planning, and public engagement, while machine learning techniques support traffic forecasting and multimodal integration. However, persistent challenges include data interoperability, model validation, and insufficient stakeholder engagement. We identify a hierarchy of mobility modes where public transit and active mobility outperform private vehicles in sustainability and user satisfaction. Integrating electrification and automation and sharing models with data-informed governance can enhance urban liveability. We propose actionable pathways leveraging Big Data and AI, outlining the roles of various stakeholders in advancing sustainable urban mobility futures. Full article

The global urgency to mitigate climate change by reducing transport-related emissions drives the accelerated electrification of road freight transport. This paper presents a comprehensive meta-study forecasting the development and corresponding power demand of electric trucks and tractor units in Hamburg up to 2050, emphasizing the shift from conventional to electric vehicles. Utilizing historical registration data and existing commercial and institutional reports from 2007 to 2024, the analysis estimates future distributions of electric heavy-duty vehicles across Hamburg’s 103 city quarters. Distinct approaches are evaluated to explore potential heavy-duty vehicle distribution in the city, employing Mixed-Integer Linear Programming to quantify and minimize distribution uncertainties. Power demand forecasts at this detailed geographical level enable effective infrastructure planning and strategy development. The findings serve as a foundation for Hamburg’s transition to electric heavy-duty vehicles, ensuring a sustainable, efficient, and reliable energy supply aligned with the city’s growing electrification requirements. Full article

The accelerated growth of the transport sector has increased oil consumption and greenhouse gas (GHG) emissions, intensifying global environmental challenges. The electrification of transportation has emerged as a key strategy to achieve sustainability targets, with electric vehicles (EVs) expected to account for 50% of global car sales by 2035. However, widespread adoption requires smart infrastructure capable of enabling dynamic in-motion charging. In this context, Electric Road Systems (ERSs), particularly those based on Wireless Power Transfer (WPT) technologies, offer a promising solution by transferring energy between road-embedded transmitters and vehicle-mounted receivers. This study assesses the structural response and service life of conventional and electrified asphalt pavement sections representative of the Spanish road network. Several standard pavement configurations were analyzed under heavy traffic (dual axles, 13 tons) using a hybrid approach combining mechanistic–empirical multilayer modeling and three-dimensional Finite Element Method (FEM) simulations. The electrified designs integrate prefabricated charging units (CUs) placed at a 9 cm depth, disrupting the structural continuity of the pavement. The results reveal stress concentrations at the CU–asphalt interface and service life reductions of up to 50% in semiflexible pavements. Semirigid sections performed better, with average reductions close to 40%. These findings are based on numerical simulations of standard Spanish sections and do not include experimental validation. Full article

Urban form optimization is crucial for controlling carbon emissions. Taking Shenzhen as a case study with 2022 data, this research constructs a multidimensional indicator system covering land use, functional mix, transportation structure, and spatial layout. It incorporates both static (inventory-based) and dynamic (transit-based) carbon efficiency metrics to capture complementary urban emission patterns. We employed OLS, GWR, and quantile regression methods to identify key influencing factors, spatial variations, and their impact on carbon emission efficiency. Results show that (1) compact road infrastructure and dense transit systems in the southwestern core contribute to higher efficiency, whereas extensive green coverage in eastern areas facilitates carbon sequestration; (2) elevated population and building densities in central zones are linked with lower efficiency, implying the necessity for balanced spatial redistribution and peripheral infrastructure enhancement; (3) despite comprehensive transit electrification, further improvements in network density and accessibility are essential to enhance urban low-carbon outcomes. These results establish a basis for optimizing urban spatial layout and reducing carbon emissions. Full article

This paper discusses the development of baseline and mitigation scenarios to guide the creation of a long-term plan supporting low-carbon transport in Ethiopia. Developing this method involved comprehensively reviewing policy documents, collecting historical activity data, and modelling the baseline and mitigation scenarios. The paper emphasises the importance of stakeholder engagement, which is instrumental in validating the model inputs, policy targets, and results at each stage, ensuring the credibility and robustness of our findings. The scenario development and analysis are based on the IPCC guidelines, informed by the policies of the Government of Ethiopia, and implemented with the Low-Energy Analysis Platform (LEAP). Three net-zero scenarios are assessed for the time horizon between 2020 to 2050. The so-called maximum ambition, NDC-aligned, and late action scenarios reflect the energy requirements and emissions contribution for varying levels of government ambition towards low-carbon interventions in the transport sector. In the baseline scenario, the total amount of carbon emissions is estimated at 4.81 million tonnes of CO₂e in 2020, which is projected to increase to over 15 million tonnes by 2050. Under the mitigation scenarios, significant reductions are projected, with specific interventions like electrification in road freight reducing emissions by 9.68 MtCO₂e and expanding rail transport reducing 9.95 MtCO₂e by 2050 compared to the baseline. Other strategies identified for mitigating transport sector emissions, like improving energy efficiency, encouraging mass transit and non-motorised transport, show good potential for achieving a greener future. With the transport sector in Ethiopia identified as a major contributor to GHG emissions and climate change, this paper underscores the government’s efforts to ensure the long-term sustainability of its transport sector. Full article

The rapid development of electric vehicles (EVs) around the world has resulted in new challenges for road safety. Identifying the features of EV crashes is a precondition for developing effective countermeasures. However, due to the short history of EV development, existing studies on EV crashes are quite limited. China, which has the largest EV market in the world, has witnessed a substantial increase in EV crashes in recent years. Therefore, this study comprehensively investigated the characteristics of EV crashes by analyzing the 2023 traffic crash data from Changshu. This is a pioneering study that discusses EV safety by comparing real EV crashes and ICEV crashes from a city in China, the largest EV market in the world. It was found that EV crashes had a higher fatality rate compared to internal combustion engine vehicle (ICEV) crashes. Compared to ICEV crashes, EV crashes are more likely to hit pedestrians and occur during the starting phase. Among the vehicles involved in crashes, the proportion of EVs used for passenger and freight transport was higher than that of ICEVs. In addition, for EV crashes, the proportion of female drivers was much higher, but the proportion of elderly drivers was much lower. Thus, to identify the significant factors influencing crash severity, a logistic regression model was built. The results confirm that EV crashes are more likely to be more fatal than ICEV crashes. In addition, hitting pedestrians and light trucks and crashes occurring in rural areas, at intersections, during winter, and on weekdays could significantly increase the risk of fatalities. These findings are expected to provide new perspectives for improving EV safety within the wave of automotive electrification. Full article

Heavy goods transportation is responsible for around 27% of CO₂ emissions from road transport in the EU and for 5% of total CO₂ emissions in the EU. The decarbonization of long-distance transport in particular remains a major challenge. The combination of battery electric trucks (BETs) with on-route high-power charging (HPC) offers a promising solution. Planning and setting up the required infrastructure is a critical success factor here. We propose a methodology to evaluate the charging infrastructure needed to support the large-scale introduction of heavy-duty BETs in Germany, considering different levels of electrification, taking the European driving and rest time regulations into account. Our analysis employs MATSim, an activity-based multi-agent transport simulation, to assess potential bottlenecks in the charging infrastructure and to simulate the demand-based distribution of charging stations. The MATSim simulation is combined with an extensive pre-processing of transport-related data and a suitable post-processing. This approach allows for a detailed examination of the required charging infrastructure, considering the impacts of depot charging solutions and the dynamic nature of truck movements and charging needs. The results indicate a significant need to augment HPC with substantial low power overnight charging facilities and highlight the importance of strategic infrastructure development to accommodate the growing demand for chargers for BETs. By simulating various scenarios of electrification, we demonstrate the critical role of demand-oriented infrastructure planning in reducing emissions from the road freight sector until 2030. This study contributes to the ongoing discourse on sustainable transportation, offering insights into the infrastructure requirements and planning challenges associated with the transition to battery electric heavy-duty vehicles. Full article

The imperative for electrification of road transport, driven by global climate targets, underscores the need for innovative powertrain systems in heavy-duty vehicles. When developing new electric drive modules, individual operational requirements need to be considered instead of generalized usage profiles, as heavy-duty vehicles experience significantly differing loads depending on their field of operation. Real driving data, representing the demands of different application scenarios, offers great potential for digital replication of driving conditions at different stages of simulation and physical validation. Application- and vehicle-specific longitudinal requirements during operation are particularly relevant for the dimensioning of powertrain components. Road gradient and mass estimation assist in the description of these operating conditions, allowing for detailed modeling of the real load conditions. An incorporation of real driving data instead of solely relying on standardized cycles has the potential of tailoring components to the target lead users and applications. While some operating conditions can be recorded by vehicle manufacturers, these are usually not accessible by third parties. In this paper, the authors present an innovative methodology of estimating vehicle parameters for the generation of representative driving profiles for implementation into a consecutive powertrain design process. The approach combines the measurement of real driving data with state estimation. The authors show that the presented methodology enables the generation of driving profiles with less than 25% deviation from the original data set. Full article

Regarding the decision to opt for vehicles with electric propulsion systems to achieve a sustainable future, much research has focused on the electrification of passenger cars, since this class of vehicles is the largest contributor of greenhouse gas emissions in the transportation sector. The purpose of this paper is to assess the energy performance of an electric vehicle used as a taxi in Loja, Ecuador, an intermediate Andean city, using a model-driven approach. Data acquisition was performed through the OBDII port of the KIA SOUL EV for 24 days and the variable mass of the vehicle was recorded as a function of the number of passengers; the effects of road gradient were also considered. The energy performance of the vehicle was simulated by developing an analytical model in MATLAB/Simulink. An average measured battery performance of 8.49 ± 1.4 km/kWh per day was obtained, where the actual energy regenerated was 31.2 ± 1.5%. To validate the proposed model, the results of the daily energy performance estimated with the simulation were compared with those measured in real driving conditions. The results demonstrated a Pearson correlation coefficient of 0.93, indicating a strong positive linear dependence between the variables. In addition, a coefficient of determination of 0.86 and a mean absolute percentage error of 3.35% were obtained, suggesting that the model has a satisfactory predictive capacity for energy performance. Full article

Transport drives economies. This statement covers complex and multifaceted economic, environmental, and political issues. The literature mainly describes the unidirectional impact of transport on the economy, and far less often bilateral or reverse impacts. This is the context in which this study was conducted. The question of whether the economy (GDP and exports and imports) and energy prices (crude oil and diesel) have an impact on road and rail transport in Poland was examined. The research was based on correlation methodology and VAR modelling for the January 2010–March 2024 period (quarterly data). It was found that there is no sufficiently strong basis to speak of an inverse relationship, i.e., that the economy is the cause of transport. This confirms the majority of studies, but it has been shown that this relationship occurs in the current period. And this statement means that both road transport, which is developing, and rail transport, which is declining in Poland, are able to serve the economy on a continuous basis. Moreover, rail transport is positively affected by changes in fuel prices, but the basic energy resource used in rail transport is not fuel but electricity. Therefore, as fuel prices rise, investment in rail transport or combined transport can have positive economic and environmental effects in the future. Full article

Charging infrastructure is the backbone of electromobility. Due to new charging behaviors and power distribution and charging space constraints, the energy demand and supply patterns of electromobility and the locations of current refueling stations are misaligned. Infrastructure developers (charging point operators, fleet operators, grid operators, vehicle manufacturers, and real-estate developers) need new methodologies and tools that help reduce the cost and risk of investments. To this extent we propose a transport-energy-demand-centric, dynamic adaptive planning approach and a data-driven Spatial Decision Support System (SDSS). In the SDSS, with the help of a realistic digital twin of an electrified road transport system, infrastructure developers can quickly and accurately estimate key performance measures (e.g., charging demand, Battery Electric Vehicle (BEV) enablement) of a candidate charging location or a network of locations under user-specified transport electrification scenarios and constraints and interactively and continuously calibrate and/or expand their network plans as facts about the deep uncertainties about the supply side of transport electrification (i.e., access to grid capacity and real-estate and presence of competition) are gradually discovered/observed. This paper describes the components and the planning support of the SDSS and how these can be used in competitive and collaborative settings. Qualitative user evaluations of the SDSS with 33 stakeholder organizations in commercial discussions and pilots have shown that both transport-energy-demand-centric and dynamic adaptive planning of charging infrastructure planning are useful. Full article

The transition towards sustainable energy systems is a key challenge faced by society. Among the different sectors, road transport becomes one of the most difficult due to the large energy consumption and infrastructure requirements. In this context, although zero-tailpipe-emission vehicle adoption is seen as a promising route, the energy provision through renewable sources is still uncertain, especially with hydrogen. This paper explores a 100% renewable energy supply scenario for both power-generation and road transport sectors in the isolated system of Tenerife. With this aim, the island’s energy system has been modelled in the software EnergyPLAN. Taking as reference the current renewable technology roadmap in the island, the impact of a full deployment of zero-tailpipe-emission vehicles on the energy system has been evaluated, providing the power and energy storage capacity requirements. The obtained results indicate the need for 6 GW of renewable power (nearly 20 times the current figures) and 12 GWh of a yet non-existent storage capacity. This deployment must be accompanied with approximately 1 GW of dispatchable sources and 1.3 GW of electrolysis capacity to carry out a complete decarbonisation of the transport sector in the island. Finally, a series of recommendations to policy makers are suggested to support the definition of future roadmaps. Full article

Hydrogen mobility embodies a promising solution to address the challenges posed by traditional fossil fuel-based vehicles. The use of hydrogen in small heavy-duty road vehicles based on internal combustion engines (ICEs) may be appealing for two fundamental reasons: Direct electrification seems less promising in heavy-duty transport systems, and fuel cell-based hydrogen vehicle implementation may not proceed at the expected pace due to higher investment costs compared to ICEs. On the other hand, hydrogen combustion is gaining attractiveness and relies on robust and cheap technologies, but it is not the only renewable solution. In this framework, this work presents a methodology to assess the Well-to-Wheel primary energy consumption and CO₂ emissions of small heavy-duty vehicles. The methodology is applied in a real case study, namely a passenger coach traveling on a 100 km mission in non-optimized conditions. Therefore, the suitability of hydrogen is compared with standard diesel and other alternative diesel-type fuels (biodiesel and synthetic diesel types). Hydrogen shows competitivity with standard diesel from the point of view of CO₂ emission reduction (−29%) while it hides a higher primary energy consumption (+40%) based on the current power-to-hydrogen efficiency declared by electrolyzer manufacturers. Nonetheless, HVO brings the highest benefits both from the point of view of primary energy consumption and emission reduction, namely −35% and 464–634 kg_CO2/100km avoided compared to hydrogen. Moreover, the availability of HVO—like other biofuels—does not depend on carbon from CO₂ capture and sequestration systems. Full article