Search Results (238)

Against the backdrop of China’s “dual-carbon” initiative, this study innovatively applies a process-based life cycle assessment (PLCA) methodology, meticulously tracking energy and carbon flows across material production, transportation, and maintenance processes. By comparing six asphalt pavement maintenance technologies in Xinjiang, the research reveals that milling and resurfacing (MR) exhibits the highest energy consumption 250,809 MJ/10³ m²) and carbon emissions (15,095.67 kg CO₂/10³ m²), while preventive techniques like hot asphalt grouting reduce emissions by up to 87%. The PLCA approach uncovers a critical insight: 40–60% of total emissions originate from the raw material production phase, with cement and asphalt identified as primary contributors. This granular analysis, unique in regional road maintenance research, challenges traditional assumptions and emphasizes the necessity of upstream intervention. By contrasting reactive and preventive strategies, the study validates that early-stage maintenance aligns seamlessly with circular economy principles. Tailored to a local arid climate and vast transportation network, the study concludes that prioritizing preventive maintenance, adopting low-carbon materials, and optimizing logistics can significantly decarbonize road infrastructure. These region-specific strategies, underpinned by the novel application of PLCA, not only provide actionable guidance for local policymakers but also offer a replicable framework for sustainable road development worldwide, bridging the gap between scientific research and practical decarbonization efforts. Full article

As an important transportation hub connecting the two sides of the Yellow River, the Yellow River Grand Bridge is of great significance for strengthening regional exchanges and promoting the high-quality development of the Yellow River Basin. However, due to the complex terrain, changeable climate, high sediment concentration, long construction duration, complicated process, strong dynamic, and many factors affecting construction. It often brings many problems, including low quality, waste of resources, and environmental pollution, which makes it difficult to achieve the balance of multiple objectives at the same time. Therefore, it is very important to carry out multi-objective optimization research on the construction of the Yellow River Grand Bridge. This paper takes the Yellow River Grand Bridge on a highway as the research object and combines the concept of “green construction” and the national policy of “carbon neutrality and carbon peaking” to construct six major construction projects, including construction time, cost, quality, environment, resources, and carbon emission. Then, according to the multi-attribute utility theory, the objectives of different attributes are normalized, and the multi-objective equilibrium optimization model of construction time-cost-quality-environment-resource-carbon emission of the Yellow River Grand Bridge is obtained; finally, in order to avoid the shortcomings of a single algorithm, the particle swarm optimization algorithm and the simulated annealing algorithm are combined to obtain the simulated annealing particle swarm optimization (SA-PSO) algorithm. The multi-objective equilibrium optimization model of the construction of the Yellow River Grand Bridge is solved. The optimization result is 108 days earlier than the construction period specified in the contract, which is 9.612 million yuan less than the maximum cost, 6.3% higher than the minimum quality level, 11.1% lower than the maximum environmental pollution level, 4.8% higher than the minimum resource-saving level, and 3.36 million tons lower than the maximum carbon emission level. It fully illustrates the effectiveness of the SA-PSO algorithm for solving multi-objective problems. Full article

Digital Twins (DTs) are becoming essential tools for real-time decision-making in transportation systems. This paper presents a macroscopic traffic digital twin developed for a 50 km segment of the C-32 interurban highway in Spain. The digital twin replicates highway conditions using real-time data from roadside sensors and connected vehicles via Vehicle-to-Everything (V2X) communications. It supports intelligent decision-making for traffic management, particularly during incident situations, by recommending macroscopic strategies such as variable speed limits and re-routing. Unlike many existing DTs focused on microscopic modeling or urban contexts, our approach emphasizes a macroscopic scale suitable for interurban highways, enabling faster computation and system-wide insights. The decision-making module evaluates candidate strategies using real-time simulations and selects the most effective option based on key performance indicators (KPIs), including congestion, travel time, and emissions. The system has been validated under realistic traffic scenarios using historical data, considering both congestion and pollution use cases. Strategies are communicated back to the physical infrastructure via V2I messages (IVIM) and a mobile application using the cellular communication network, enabling a closed-loop architecture. This paper contributes a scalable, real-time, and field-integrated macroscopic DT framework for highway traffic management. Full article

This paper examines the feasibility of transitioning road cargo to waterborne transport in the UK, aiming to reduce emissions and alleviate road congestion. Key objectives include (1) developing a modal shift technology to establish freight highways across the UK, (2) designing a small, decarbonized barge vessel concept that complements the logistics framework, and (3) assessing the economic and environmental viability of a multimodal logistics network. Using discrete event simulation (DES), four transportation scenarios were analyzed to evaluate the efficiency and sustainability of integrating coastal and inland waterways into the logistics framework. Results indicate that waterborne transport is more cost-effective and environmentally sustainable than road transport. A sweeping design study was conducted to optimize time, cost, and emissions. This model was applied to a case study, providing insights into optimal pathways for transitioning to waterborne freight by finding the optimized number of TEUs. Consequently, our study identified 96 TEUs as the optimal capacity to initiate barge design, balancing cost, time, and emissions, while 126 TEUs emerged as the best option for scalability. Findings offer critical guidance for supporting the UK’s climate goals and governmental policies by advancing sustainable transportation solutions. Full article

To explore the feasibility of renewable hybrid energy systems for expressway infrastructure, this study proposes a scenario-based design methodology integrating solar, wind, and hydropower resources within the expressway corridor. A case study was conducted on a highway service area located in southern China, where a solar/wind/hydro hybrid energy system was developed based on the proposed approach. Using the HOMER Pro 3.14 software platform, the system was simulated and optimized under off-grid conditions, and a sensitivity analysis was conducted to evaluate performance variability. The results demonstrate that the strategic integration of corridor-based natural resources—solar irradiance, wind energy, and hydrodynamic potential—enables the construction of a technically and economically viable hybrid energy system. The system includes 382 kW of PV, 210 kW of wind, 80 kW of hydrokinetic power, a 500 kW diesel generator, and 180 kWh of battery storage, forming a hybrid configuration for a stable and reliable energy supply. The optimized configuration can supply up to 1,095,920 kWh of electricity annually at a minimum levelized cost of energy of USD 0.22/kWh. This system reduces CO₂ emissions by 23.2 tons/year and NO_x emissions by 23 kg/year. demonstrating strong environmental performance and long-term sustainability potential. Full article

The intermodal express network of high-speed railways and highways can fully utilize the flexibility of highways and the advantages of high-speed railways, such as low cost, high efficiency, and low carbon emission. This paper studies the hub location and flow assignment problem in the intermodal express network of high-speed railways and highways, which can not only increase the transportation efficiency but also provide door-to-door service. Considering the characteristics of multiple modes, flow balance, carbon emission, capacity constraints, and time constraints in the intermodal express network, a mixed-integer linear programming model is proposed with the objective of minimizing the total cost by determining the hub locations, allocations, mode selections, and flow assignments. Owing to the NP-hard computational complexity, an improved genetic algorithm with local search is designed by combining the genetic operators and two optimization strategies to solve the problem effectively. Lastly, numerical experiments are conducted to validate the feasibility of the model and the effectiveness of the algorithm. Full article

The motorized vehicle methodology in the Highway Capacity Manual (HCM) does not account for the effect of left-turn bay overflow, which is stated as a limitation of the methodology. In this study, an adjustment factor was developed to quantify the impact of left-turn bay length on the through lane capacity at signalized intersections. The adjustment factor was modeled based on a large number of scenarios generated using the CORSIM microsimulation model. These scenarios covered intersection geometries typical for two-phase signal control and included a wide range of traffic parameters (number of lanes, traffic volume, left-turn volume, left-turn bay length, cycle length, and green ratio). By comparing the capacity values obtained with a short left-turn bay to those with an infinitely long bay under identical other traffic conditions, it was possible to develop an adjustment factor that reflects the impact of turn bay overflow. A regression-based model was created and validated, showing very good agreement with the simulated values. The new adjustment factor provides an enhancement of the HCM estimation methodology that improves the accuracy of capacity and delay estimates in intersection evaluations as well as supports more effective intersection design and sustainable mobility. More accurate capacity estimation reduces congestion, travel delays, and vehicle stopping, directly contributing to sustainable transportation goals, lowering emissions, and supporting environmentally responsible urban mobility systems. Full article

The energy transition of the road transport sector is now a strategic priority for achieving global decarbonization targets. In particular, the highway sector offers the opportunity to integrate sustainable solutions without additional land consumption, thanks to the availability of relevant areas that are already covered by infrastructure. This study proposes a large-scale analysis of the potential photoelectric energy that can be produced within highway infrastructures, with the aim of evaluating the contribution that these assets can make to electric mobility. The analysis was conducted using geographic information systems (GISs), applied to the case study of the A3 Napoli–Pompei–Salerno highway. The processing of topographical, orographic, and solar data has made it possible to identify a total surface area of approximately 27,100 m² that is potentially suitable for the installation of photovoltaic systems, distributed among service areas, toll stations, car parks, and side sections. This result highlights the concrete possibility of making the most of the energy potential of highway infrastructure, promoting self-production and local consumption models to power the electric vehicle charging network, thus contributing directly to the reduction of emissions and the sustainability of the transport system. Full article

(1) Background: Road traffic emissions significantly influence heavy metal accumulation in roadside agricultural soils, posing risks to food safety. (2) Methods: This study investigated the concentrations of heavy metals (As, Cd, Cu, Cr, Hg, Ni, Pb, and Zn) in paddy soils at 96 soil samples along National Highways G107 and G312 in southern Henan, China, to evaluate the contamination situation and ecological risks using a multimetric approach. (3) Results: Cd, Hg, Cu, and Zn exceeded provincial background levels. Cd dominated contamination, showing heavy pollution (single factor index, P_i > 5) within 40 m of G107 and moderate/heavy levels (P_i = 2–5) along G312. The Nemerow index (P_N) classified both highways as slightly polluted (P_N = 0.70–0.81), with higher contamination along G107. Geoaccumulation indices identified Cd as mildly/moderately polluted within 40 m of G107 and G312 and Zn as slightly contaminated within 20–40 m of G107. Despite low total ecological risk, Cd contributed >75% to cumulative risk due to its high toxicity (Tr = 30). (4) Conclusions: Road traffic constitutes one of the contributors to heavy metal accumulation in paddy soils along national highways in southern Henan Province, while agricultural cultivation adjacent to transportation corridors poses potential food safety risks. Full article

With rising urgency around carbon emissions and climate change, electrification has emerged as a central focus in traditionally combustion-reliant industries. With increasing regulatory restrictions on automotive and smaller off-highway markets (<25 hp), the heavy equipment industry faces growing pressures to adopt hybrid and fully electric solutions. Current literature primarily addresses technical electrification challenges, leaving a gap in understanding industry perspectives. This study explores trends, challenges, and expectations of electrification from industry representatives’ viewpoints, using data from 84 surveys conducted at the CONEXPO/CONAGG trade show and sentiment analysis of 100 interview notes gathered through an NSF Innovation Corps workshop. Results indicate substantial uncertainty toward electrification, with key limitations including power-to-weight ratios, high costs, maintenance, leakage concerns, and reliability of electronic components. The majority (77%) preferred traditional hydraulic systems due to familiarity and reliability, though concerns over maintenance and environmental impact remain prevalent. Participants anticipate a gradual industry transition, projecting widespread adoption of hybrid solutions in 10–15 years and longer timelines for fully electric systems. Effective adoption of greener technologies is likely through industry-wide standards and financial incentives. This study emphasizes the industry’s cautious yet gradually increasing openness to electrification amidst persistent technological and economic challenges. Full article

Increasing traffic loads, extreme climatic conditions, and environmental regulations highlight the need to re-evaluate the use of existing asphalt binders in pavement construction. This paper examines the limitations of conventional and modified asphalt binders by incorporating a comprehensive literature review that focuses on performance, environmental impact, and economic issues. Studies show that binder grade selection, mixing and compaction temperatures, and ageing affect pavement performance and may reduce pavement service life by 10% to 30%. Although modifiers such as polymers and nanomaterials can improve rutting and moisture damage resistance by up to 50%, they have limited effects on fatigue and thermal cracking resistance. Moreover, these modifiers can affect the asphalt mixture production process due to source variability, leading to complex mixing methods, increased cost, and higher emissions. Additionally, high-temperature asphalt mixture production increases air pollution by 250%, causing health risks. Furthermore, asphalt binder and mixture production account for over 50% of the total pavement costs, and the rising asphalt binder prices place a burden on highway budgets. This review highlights the critical research gaps including source variability, testing and mixing methods, and environmental impact of modifiers and provides a future roadmap for developing cost-effective and sustainable alternatives and their practical implementation. Full article

Given the differing interests and demands of various participants in multimodal transportation, this paper proposes a multi-attribute decision-making method driven by user preferences. Firstly, a four-dimensional optimization model is established with the objectives of minimizing transportation costs, transportation time, carbon emissions, and transportation risks. Furthermore, considering the practical aspects of transportation, differentiated time window constraints are designed based on the continuous time windows of highway transportation, railway train schedules, and the arrival and departure time characteristics of waterway vessels. In terms of solution methods, an improved Genetic Algorithm (GA) and Aptenodytes Forsteri Optimization (AFO) hybrid algorithm (GA-AFO) is proposed, which introduces GA to generate a high-quality initial population to accelerate convergence. By replacing the traditional gradient estimation strategy with a random mutation strategy based on probability distribution, the local search mechanism of AFO is enhanced. Furthermore, in response to the aforementioned multi-objective problem, a multi-attribute decision-making method is devised to reconcile the subjective preferences of decision makers with objective weights, thereby yielding more scientifically valid decision outcomes. Numerical experiments have shown that the designed hybrid algorithm can quickly find solutions and demonstrates good robustness. The proposed multi-attribute decision-making method is able to generate decision schemes tailored to the preferences of different decision makers, thus providing a scientific basis for the formulation of personalized transportation schemes. Full article

With the widespread adoption of highways in the mountainous regions of southwestern China, the electricity load of numerous tunnels and service areas has increased rapidly. Constructing photovoltaic (PV) microgrids in service areas has become an important means of energy conservation, consumption reduction, and carbon emission mitigation. However, constrained by mountainous terrain, the PV power generation conditions in highway service areas exhibit significant micro-terrain variations, making it difficult to effectively evaluate PV utilization efficiency. This paper proposes a dynamic block optimization model for PV microgrids that considers regional layout constraints. The model utilizes an intelligent adjustment mechanism to plan PV panel layouts in highway service areas, optimizing energy utilization efficiency and economic benefits. Additionally, long short-term memory (LSTM) networks are employed for short-term PV output prediction to address the challenges posed by varying weather and seasonal changes. This approach comprehensively considers the intermittency and instability of PV power generation, enabling dynamic block optimization to autonomously adjust the PV power output in response to load fluctuations. Through simulation case studies, the model is validated to effectively improve the utilization rate and economic performance of PV microgrids under various environmental conditions and demonstrates superior performance compared with traditional static block methods. Full article

The Fuzzy-Set Qualitative Comparative Analysis (fsQCA) method is employed in this study to investigate the combined effects of region area, the number of COVID-19 infections, and the number of family cars on NO₂ concentration at key highway toll stations in Zhejiang Province, China. By selecting and comparing typical cases, the analysis reveals differentiated characteristics in how various factor combinations influence NO₂ concentration. The main findings are as follows: Under COVID-19 lockdown measures, prolonged vehicle waiting times and a shift towards family car usage among the public have led to a significant increase in NO₂ concentration at highway toll stations. Promoting the Electronic Toll Collection (ETC) system and encouraging public transportation are of great importance. The synergistic effects of COVID-19 lockdown policies and urban land area, resulting in the reduction in the number of family cars and the excellent air circulation conditions in large cities, have contributed to the decrease in NO₂ concentration at highway toll stations. Increasing urban green spaces and promoting clean energy vehicles are crucial for advancing urban sustainable development. The combined analysis of the region area and the number of family cars indicates that a higher proportion of large vehicles contributes to improving transportation efficiency, but also results in elevated NO₂ concentration at highway toll stations due to diesel emissions. Optimizing the transportation structure and reducing reliance on large vehicles are of significant importance. Full article

Many cities are still struggling to comply with current air quality regulations. Road transport is usually a significant source of NOx emissions, especially in urban areas. Therefore, NOx from road vehicles needs to be further reduced below current standards to ultra-low or even zero-impact levels. In a novel, holistic powertrain design approach, this paper presents powertrain solutions to achieve zero-impact NOx emissions with an N1 class III diesel light commercial vehicle. The design is based on a compliance test matrix consisting of six real-world scenarios that are critical for emissions and air quality. As a design baseline, a vehicle concept meeting the emission requirements as set out in the European Commission’s 2022 Euro 7 regulation proposal is used. The baseline vehicle concept can achieve zero-impact NOx emissions in 67% of these scenarios. To achieve zero-impact NOx emissions in all scenarios, further advanced emission solutions are mandatory. In congested urban areas, the use of an exhaust gas aftertreatment system preheating device with at least 20 kW of power for 1 min is required. In high-traffic highway situations, an underfloor SCR unit with a minimum volume of 12 l or the restriction of the maximum vehicle speed at 130 km/h is required. Full article