Search Results (1,570)

Transport is among the fastest-growing contributors to carbon dioxide (CO₂) emissions in the Gulf Cooperation Council (GCC) region, where rapid urbanization, population growth, and high mobility demand continue to shape energy use. This study aims to quantify the extent to which economic growth and urbanization drive transport-related CO₂ emissions across Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates between 2012 and 2022. Using sector-specific data from the International Energy Agency and World Bank, we apply panel and country-level log–log regression models to estimate long-run and short-run elasticities of transport CO₂ emissions with respect to GDP and urban population. The analysis also includes robustness checks excluding the COVID-19 pandemic year to isolate structural effects from temporary shocks. Results show that transport emissions remain strongly correlated with GDP in most countries, indicating emissions-intensive growth, while the influence of urbanization varies: positive in Kuwait and Saudi Arabia, where expansion is car-dependent, and negative in Oman and Qatar, where compact urban forms and transit investments mitigate emissions. The findings highlight the importance of differentiated policy responses—fuel-pricing reform, vehicle efficiency standards, electrification, and transit-oriented planning—to advance low-carbon mobility. By integrating elasticity-based diagnostics with decoupling analysis, this study provides the first harmonized empirical framework for the GCC to assess progress toward transport-sector decarbonization. Full article

The electrification of non-road mobile machinery is advancing to enhance sustainability and reduce emissions. This study investigates how to maximize the efficiency of the retrofitting of a material handler from an internal combustion engine to a battery-powered electric motor, while keeping the hydraulic system unchanged. Using a previously validated model, this study proposes three control strategies for the electric motor and hydraulic pump to enhance efficiency and performance. The first control strategy optimizes hydraulic pump performance within its most efficient displacement range. The second strategy maximizes powertrain efficiency by considering both efficiencies of the electric motor and hydraulic pump. The third strategy uses a servo-actuated valve to adjust the load-sensing margin and exhibits energy savings up to 14.2% and an 11.5% increase in efficiency. The proposed strategies avoid complex optimization algorithms, ensuring practical applicability for small- and medium-sized enterprises, which often face cost constraints and limited scalability. Full article

The decarbonization of regional passenger rail transport is one of the key challenges for the sustainable transformation of the transport sector in Poland. While railway transportation remains one of the least carbon-intensive modes of transport, significant emission disparities persist between electrified and non-electrified lines, where diesel traction is still prevalent. This article presents a comparative analysis of various propulsion technologies—diesel, hybrid, battery-electric and hydrogen fuel-cell—taking into account both local (TTW) and total (WTW) greenhouse gas emissions. The study incorporates Poland’s current energy mix and proposes a methodological framework to assess emissions at the line level. It highlights the risks of focusing exclusively on in situ zero-emission technologies and calls for a more flexible, efficiency-based approach to fleet modernization. The analysis demonstrates that hybrid and optimized combustion-based systems can provide substantial emission reductions in the short term, especially in rural and transitional regions. The paper also critically discusses transport funding policies, pointing to discrepancies between incentives for private electric mobility and the lack of support for public transport solutions that could effectively counter mobility exclusion. The presented methodology and conclusions provide a basis for further research on transport decarbonization strategies tailored to national and regional contexts. Full article

Biochar is increasingly recognized as a multifunctional soil amendment that improves soil fertility, nutrient cycling, and crop productivity. Studies across field, greenhouse, and incubation settings show that biochar enhances nutrient retention, reduces leaching, and regulates carbon, nitrogen, and phosphorus cycling. Its effects are shaped by intrinsic physicochemical properties and interactions with soil minerals, microbial communities, and enzymatic processes. Short-term benefits of biochar applications often include improved nutrient adsorption and water regulation, while long-term applications support stable soil organic matter formation, root development, and fertilizer use efficiency. Biochar also reshapes soil microbial diversity and activity. Beneficial bacterial groups such as Proteobacteria and Actinobacteria, along with fungi such as Mortierella, respond positively, enhancing nitrogen fixation, phosphorus solubilization, and organic matter decomposition. Meanwhile, biochar applications could suppress pathogens. Enzyme activities, including urease and phosphatase, are typically stimulated, driving nutrient mobilization. Yet outcomes remain context-dependent, with biochar feedstock, application rate, soil conditions, and crop type influencing results; excessive use may suppress enzymatic activity, reduce nutrient availability, or shift microbial communities unfavorably. Practically, biochar can improve fertilizer efficiency, restore degraded soils, and reduce greenhouse gas emissions, contributing to climate-smart agriculture. Future work should prioritize long-term, multi-site trials and advanced analytical tools to refine sustainable application strategies. Full article

The transportation sector is responsible for over 20% of Europe’s CO₂ emissions, significantly worsening urban air quality and compromising public health. Electric vehicles (EVs)—namely BEVs and PHEVs—offer some relief by lowering noise and pollution in urban settings. Nevertheless, their effectiveness in benefiting the environment relies on the current electricity generation mix. In accordance with national energy goals, this study evaluates the environmental effects of EV adoption in Greece until 2035, utilizing a scenario-based approach grounded in the forecasts of the Greek National Energy and Climate Plan. Three different electrification pathways are examined to explore how varying levels of electric vehicle adoption and progress in decarbonizing the power sector could reduce air pollution, particularly in cities. By comparing the projected CO₂, CO, NO_x, PM₁₀, and SO₂ pollutant output from BEVs and PHEVs with those of internal combustion engine vehicles, the study highlights the significance of integrating renewable energy sources and assesses the potential for EVs to reduce emissions within Greece’s changing energy mix. Full article

Transportation is one of the major carbon dioxide (CO₂)-emitting industries, facing substantial reduction pressure under low-carbon sustainable development. Cities are key to reducing transportation CO₂ emissions, and the Low-Carbon City Pilot Policy (LCCPP) is essential to advance the development of low-carbon cities and achieve peak-carbon and carbon-neutral targets. In this paper, we analyse the effect of the LCCP on transportation CO₂ emissions using a multiperiod difference-in-differences (DID) method with data from 284 Chinese cities between 2006 and 2020. The results indicate a substantial reduction in urban transportation CO₂ emissions through the LCCP, and that the enhancement of urban public transportation levels and residents’ green mobility are effective ways to accomplish this. This conclusion is upheld after conducting various robustness tests. Examination of the heterogeneity of the results and spatial analysis revealed that the LCCPP significantly reduced transportation CO₂ emissions in eastern, western, and low-economy cities in China, but not in central and high-economy cities, that the reduction effect was better for southern, non-resource-based cities than for northern, resource-producing cities, and that it exerted notable spillover effects in surrounding cities. The results of this paper offer valid policy insights and practical guidance to maximise the CO₂ reduction effects of the LCCP in the transportation sector. Full article

Road damage threatens driving safety, making timely maintenance essential. However, conventional repairs require on-site personnel, necessitating traffic control and lane closures. These restrictions cause traffic congestion, leading to unnecessary idling and repeated acceleration and deceleration of vehicles, reducing fuel efficiency and increasing energy consumption. To overcome these limitations, this study proposes a method for performing inspections without lane closures, utilizing machine vision and AI-based damage detection technology. Furthermore, to quantitatively verify the effectiveness of the proposed method, an energy consumption analysis is conducted using the traffic simulator simulation of urban mobility (SUMO) and the vehicle energy simulator future automotive systems technology simulator (FASTSim). Results show lane closures reduced average speed by 25% and increased driving time by over 40%, adding 5044.73 L of fuel for gasoline vehicles and 3208.63 L for diesel vehicles, with CO₂ emissions rising by 11.86 and 8.60 t, respectively. In contrast, the proposed method had minimal traffic impact, with less than 0.1% increases in fuel use and emissions. This approach enables simultaneous multi-lane inspection, improving maintenance efficiency and reducing social costs and energy waste caused by traffic control. Full article

Urban trees play a critical role in mitigating climate change by capturing atmospheric CO₂ and providing multiple co-benefits, including cooling urban environments, reducing building energy demand, and enhancing citizens’ physical and psychological well-being. This study presents the Co Carbon Trees Measurement project, a citizen science initiative implemented in the city of Viladecans, Spain, involving 658 students, local administration, and academia, three components of the EU mission’s quadruple helix governance model. Over one year, 1274 urban trees were measured for trunk diameter and height to quantify annual CO₂ sequestration using a direct measurement approach combining field data collection with a mobile application for a height assessment and a flexible measuring tape for diameter. Results indicate that carbon fixation increases with tree size, displaying a parabolic function with larger trees sequestering significantly more CO₂. A range between 10 and 20 kg of CO₂ is sequestered by the urban trees in the period 2024–2025. The study also highlights the broader benefits of urban trees, including shading, mitigation of the urban heat island effect, and positive impacts on mental health and social cohesion. While the total CO₂ captured in Viladecans (≈810 tons/year) is small relative to city emissions (≈170,000 tons/year), the methodology demonstrates a scalable, replicable approach for monitoring progress toward climate neutrality and integrating urban trees into planning and climate action strategies. This approach positions green infrastructure as a central component of sustainable and resilient urban development. Full article

Sustainable mobility policies are unlikely to succeed without efforts to tackle disagreement between different social groups. In this context, we describe a participatory process based around semi-structured interviews with expert stakeholders in sustainable mobility in the city of Madrid. Information elicited from interviews was structured using the Natural Step approach, based on detailed analysis of stakeholder discourse, into four scenarios of sustainable mobility: Remote Working, The 15-min City, Electric City and Public City. Subsequently, the four scenarios were subject to critical analysis by a second group of experts during a stakeholder workshop. The Remote Working scenario was considered a partial solution applicable to only ~30% of the population and saved commuter trips might be canceled out by increased mobility elsewhere. The 15-min City was seen as desirable but utopian and dependent on political consensus and major public investment. The Electric City was thought useful for reducing emissions but hard to implement due to infrastructure limitations and cost. The Public City was seen as an integrated vision from which other solutions should flow but also politically divisive. While no single scenario was unanimously backed by all participants, different coalitions of interest tended to support different approaches. Collectively, the four scenarios reveal divergent pathways to the same goal (a more sustainable city), suggesting ways forward for policy. Full article

Despite increasing interest in AI, IoT, and blockchain for sustainable transportation, existing reviews remain fragmented—focusing on single technologies, descriptive benefits, or narrow applications—without providing an integrated synthesis across domains. This study conducts a systematic literature review (SLR) following the PRISMA 2020 guidelines and a bibliometric analysis of 102 peer-reviewed papers to provide the concurrent integrative synthesis of AI, IoT, and blockchain in enabling sustainable transport. Data were drawn from Scopus, Web of Science, PubMed, Semantic Scholar, and Google Scholar, and analyzed using VOSviewer to identify research clusters, emerging themes, and knowledge gaps. The results reveal three thematic clusters: smart traffic systems for congestion management, sustainable logistics and supply chains, and data-driven urban governance. Across these clusters, AI is more mature in predictive modeling, IoT remains fragmented in interoperability, and blockchain is still at a pilot stage with governance and scalability issues. The analysis highlights synergies (e.g., AI–IoT integration for real-time optimization) and persistent challenges (e.g., standardization, data security). This review contributes a strategic research roadmap linking bibliometric hotspots with policy and practice implications. By explicitly identifying gaps in governance, interoperability, and cross-domain integration, the study offers actionable directions for both researchers and policymakers to accelerate digital transitions in transport. Full article

Urban air pollution caused by vehicular emissions remains one of the most pressing environmental challenges, negatively affecting both public health and climate processes. In Kokshetau, Kazakhstan, where electric vehicle (EV) adoption accounts for only 0.019% of the total fleet and charging infrastructure is nearly absent, reducing transport-related emissions requires short-term and cost-effective solutions. This study proposes an integrated approach combining urban ecology principles with computational modeling to optimize traffic signal control for emission reduction. An artificial neural network (ANN) was trained using intersection-specific traffic data to predict emissions of carbon monoxide (CO), nitrogen oxides (NO_x), sulfur dioxide (SO₂), and particulate matter (PM_2.5). The ANN was incorporated into a nonlinear optimization framework to determine traffic signal timings that minimize total emissions without increasing traffic delays. The results demonstrate reductions in emissions of CO by 12.4%, NO_x by 9.8%, SO₂ by 7.6%, and PM_2.5 by 10.3% at major congestion hotspots. These findings highlight the potential of the proposed framework to improve urban air quality, reduce ecological risks, and support sustainable transport planning. The method is scalable and adaptable to other cities with similar urban and environmental characteristics, facilitating the transition toward eco-friendly mobility and integrating data-driven traffic management into broader climate and public health policies. Full article

Tire–road friction is a fundamental factor in vehicle safety, energy efficiency, and environmental sustainability. This narrative review synthesizes current knowledge on the tire–road friction coefficient (TRFC), emphasizing its dynamic nature and the interplay of factors such as tire composition, tread design, road surface texture, temperature, load, and inflation pressure. Friction mechanisms, adhesion, and hysteresis are analyzed alongside their dependence on environmental and operational conditions. The study highlights the challenges posed by emerging mobility paradigms, including electric and autonomous vehicles, which demand specialized tires to manage higher loads, torque, and dynamic behaviors. The review identifies persistent research gaps, such as real-time TRFC estimation methods and the modeling of combined environmental effects. It explores tire–road interaction models and finite element approaches, while proposing future directions integrating artificial intelligence and machine learning for enhanced accuracy. The implications of the Euro 7 regulations, which limit tire wear particle emissions, are discussed, highlighting the need for sustainable tire materials and green manufacturing processes. By linking bibliometric trends, experimental findings, and technological innovations, this review underscores the importance of balancing grip, durability, and rolling resistance to meet safety, efficiency, and environmental goals. It concludes that optimizing friction coefficients is essential for advancing intelligent, sustainable, and regulation-compliant mobility systems, paving the way for safer and greener transportation solutions. Full article

A transition from fossil fuels to renewable energy is underway to achieve net-zero emissions. The institutional arrangements in Indonesia’s energy transportation sector are crucial for various stakeholders involved in the energy transition. This study combines historical institutionalism with a multi-level perspective to analyze how policy formulation, critical junctures, and path dependence shape institutional changes toward sustainable mobility. The evolution of institutional arrangements can be categorized into three phases: the establishment of fuel-oil-based infrastructure and dependency (1970–2003); the diversification of cleaner fuels through compressed natural gas and biofuels (2004–2014); and the development of affordable and clean energy, focusing on biofuels and electrification (2015 to present). In parallel, a quantitative total cost of ownership analysis of vehicles using different fuel types demonstrates how institutional reforms, fiscal incentives, and regulatory support reshape the economic feasibility of low-carbon technologies. Landscape pressures—such as global decarbonization, fuel import dependence, and energy security challenges—interact with niche innovations, including biofuels, electric vehicles, and hybrid systems, to drive systemic transformation. The findings indicate that institutional changes, supported by quantitative economic evidence and technology diffusion, play a pivotal role in realigning Indonesia’s transport energy regime toward a more resilient, inclusive, and sustainable transition. Full article

Effective and sustainable planning for future smart transportation systems is hindered by outdated traffic management models that fail to capture real-world dynamics, leading to congestion and significant environmental impact. To address this, advanced machine learning models are required to provide high-fidelity insights into urban mobility. In this work, we propose an adaptive machine learning approach to traffic pattern recognition that synergizes the HDBSCAN and k-means clustering algorithms. By employing a data-driven weighted voting mechanism, our solution provides a robust analytical foundation for sustainable planning, integrating structural analysis with precise cluster refinement. The crafted model was validated using a high-fidelity simulation of the Khmelnytskyi, Ukraine, transport network, where it demonstrated a superior ability to identify distinct traffic modes, achieving a V-measure of 0.79–0.82 and improving cluster compactness by 10–14% over standalone algorithms. It also attained a scenario identification accuracy of 92.8–95.0% with a temporal coherence of 0.94. These findings confirm that our adaptive approach is a foundational technology for intelligent transport systems, enabling the planning and deployment of more responsive, efficient, and sustainable urban mobility solutions. Full article

In the realm of sustainable public transportation, the integration of intelligent electric bus propulsion systems represents a novel and promising approach to reducing environmental impact—particularly through the mitigation of NOx emissions and overall exhaust pollutants. This emerging technology underscores the growing need for advanced drive control architectures that ensure not only operational safety and reliability but also compliance with increasingly stringent emissions standards. The present article introduces an innovative analysis of energy-optimized dual-drive electric propulsion systems, with a specific focus on their potential for real-world application in emission-conscious urban mobility. A detailed dynamic model of a dual-drive electric bus was developed in MATLAB Simulink, incorporating a Fuzzy Logic-based decision-making algorithm embedded within the Transmission Control Unit (TCU). The proposed control architecture includes a torque-limiting safety strategy designed to prevent motor overspeed conditions, thereby enhancing both efficiency and mechanical integrity. Furthermore, the system architecture enables supervisory override of the Fuzzy Inference System (FIS) during critical scenarios, such as gear-shifting transitions, allowing adaptive control refinement. The study addresses the unique control and coordination challenges inherent in dual-drive systems, particularly in relation to optimizing gear selection for reduced energy consumption and emissions. Key areas of investigation include maximizing efficiency along the motor torque–speed characteristic, maintaining vehicular dynamic stability, and minimizing thermally induced performance degradation. The thermal modeling approach is grounded in integral formulations capturing major loss contributors including copper, iron, and mechanical losses while also evaluating convective heat transfer mechanisms to improve cooling effectiveness. These insights confirm that advanced thermal management is not only vital for performance optimization but also plays a central role in supporting long-term strategies for emission reduction and clean, efficient public transportation. Full article