Sustainable Transport Development Research Articles

Experimental investigation on SiO2 nano particle as additives on performance and emission parameters of diesel engine fueled with castor oil blends


 
 
 
 Introduction: Today, a lot of research work is carried out in the vegetable oil based fuels which are the blended renewable fuels derived from vegetable oils or the oxygenated fuels which could effect in reduced Carbonaceous emissions. This experimental study investigates the impact of Silicon dioxide (SiO2) nanoparticles as additives on the performance and emission parameters of a diesel engine running on castor oil blends.
 
 
 
 
 Materials and methods: Castor oil is a renewable source of biodiesel, but it has limitations such as lower calorific value and higher viscosity compared to conventional diesel. To overcome these limitations, SiO2 nanoparticles were synthesized and characterized. Tests were conducted on a single-cylinder diesel engine under various load conditions using different fuel blends.
 
 
 
 
 Results: Results shows that the addition of SiO2 nanoparticles improved the engine's performance by increasing brake thermal efficiency by 25% and reducing specific fuel consumption by 9%. Carbon monoxide emissions (CO) were decreased by 25%, Hydro Carbon emissions (HC) decreased by 52% with SiO2 nanoparticles while a marginal percentage of NOx was also observed.
 
 
 
 
 Conclusion: This study demonstrates the potential of SiO2 nanoparticles as additives in enhancing the performance and reducing emissions of diesel engines using castor oil blends, contributing to the development of sustainable transportation.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Sustainable Development of Intermodal Freight Transportation—Through the Integration of Logistics Flows in Ukraine and Poland

Nowadays, sustainable development is becoming a model for significant improvements in the modern world. Taking into consideration possible future challenges, transport must have sustainable features. Today, such a type of transportation as intermodal transport (transport that uses more than one mode of transportation) is gaining relevance. It is one of the most promising types of transport from an economic and environmental point of view. In this paper, the importance of sustainable development of intermodal freight transport is analyzed; the state of foreign trade and the trade balance in Ukraine and Poland are examined; and the sustainable development trends and prospects of trade relations between two countries are determined, taking into account the existing product structure. It is noted that the post-war recovery of Ukraine will require the activation of logistical flows with EU countries. The analysis of the state of freight transport by various modes of transport allowed for theoretically justifying the insufficient attention given to the development of intermodal freight transport between Ukraine and Poland for logistics optimization in international trade. From a methodological perspective, it is proposed to describe the subject area in terms of graph theory. The practical contribution involved the testing of the proposed model of intermodal freight transport to optimize logistics flows in international trade between Ukraine and Poland, considering the minimization of transport service costs and time. This required refining the mathematical apparatus based on the method of successive moves and linking their development to specific supply chains.

СТРАТЕГИИ УСТОЙЧИВОГО РАЗВИТИЯ ГОРОДСКИХ ГРУЗОВЫХ ПЕРЕВОЗОК

The article examines strategies for the sustainable development of urban freight transport. Op-tions for urban freight and company actions that can be part of a sustainability strategy are out-lined, as well as non-freight policies that may have unintended consequences for the sustainabil-ity of urban freight. An analysis of the challenges that arise when trying to implement approach-es to increasing the sustainability of urban freight transport is providedm

Review on aerodynamic characteristics and energy recovery of vehicle platoon

Platooning can reduce air drag when driving at high speed and improve aerodynamic characteristics. It can not only improve fuel economy, driving comfort, and safety of drivers but also reduce emissions and alleviate traffic congestion. At the same time, the energy recovery of vehicle driving is also in line with the general trend of international environmental governance. It has played an active role in reducing emissions and improving the ecological environment. In this paper, the effects of vehicle longitudinal spacing, number of vehicles and crosswind on the aerodynamic performance of longitudinal and side-by-side platoons are reviewed, as well as energy recovery. The study found that the three-vehicle platoon reduces drag by 30% compared to the two-vehicle platoon. Comparing the aerodynamic drag of the three-vehicle platoon with that of the single vehicle, the drag coefficient of the first and last vehicles can be reduced by 20%, and the drag coefficient of the middle vehicle can be reduced by about 50%. As the crosswind speed and crosswind angle increase, the drag coefficient and pressure of each member in the platoon increase. Recycling wind energy through wind turbines and alternators can increase the driving range of electric vehicles by 23%. The study of the aerodynamic characteristics and energy recovery of platooning vehicles can provide direction and theoretical basics for the development and sustainable development of intelligent transportation.

Sustainable road network design considering hydrogen fuel cell vehicles

Environmental pollution and energy shortages have brought about an increased focus on new energy vehicles. Hydrogen fuel cell vehicles (HFCVs) have experienced rapid development due to the potential to alleviate energy pressures and reduce pollution emissions. Near zero-carbon emissions offer a promising avenue for promoting sustainable transportation development. To evaluate the impact of HFCVs on the transportation environment, this paper investigates the problem of sustainable transportation network design including HFCVs. Specifically, the problem is formulated as a bi-level multi-objective programming problem, with the upper level aimed at determining the optimal network design scheme considering multiple objectives, while the lower level addresses the mixed traffic flow that comprises both HFCVs and fuel vehicles. To solve the multi-objective sustainable network design problem, an integrated solution framework that combines the particle swarm optimization (PSO) algorithm with the Frank-Wolfe algorithm (FW) is developed. Specifically, the PSO algorithm is utilized to solve the upper-level model and identify the optimal network design schemes, while FW algorithm is adopted to handle mixed traffic flow assignments. Finally, the proposed model and algorithm are implemented in two numerical experiment to demonstrate their effectiveness and efficiency.

New Energy Commuting Optimization under Low-Carbon Orientation: A Case Study of Xi’an Metropolitan Area

Low-carbon travel is an important part of low-carbon cities and low-carbon transportation, and low-carbon transportation is an inevitable choice to slow down the growth of carbon emissions in China. All countries in the world are actively promoting new energy vehicles and attach great importance to the application of the new energy industry in urban transportation. Commuting is an important part of urban life, and the choice of travel behavior has an important impact on traffic and environmental protection. Taking the Xi’an metropolitan area as an example, this paper expounds on the integrated development path of the industrial chain of new energy + travel in the metropolitan area and clarifies the energy transformation model of the integrated development of low-carbon transportation and energy. From the perspective of green and low-carbon, 1000 commuters were interviewed using a questionnaire survey, and the cumulative prospect model was used to verify the internal mechanism affecting commuters in metropolitan areas to choose new energy commuting. The results of the study show that new energy transportation modes play an important role in the low-carbon economy, and under different scenarios and assumptions, there are significant differences in the cumulative prospect values of the subway, new energy buses and fuel private cars, and corresponding optimization measures are proposed to increase the proportion of new energy commuting trips. The results will help further promote the development of a low-carbon economy and energy integration in the field of transportation and provide a reference for the sustainable development of public transportation.

Sustainable development of passenger transport in Poland in the context of young passengers’ preference survey

The issue of reducing the adverse impact of transport on the environment has been reflected in key European transport documents. Their content clearly indicates that rail transport is more “environmentally friendly” than road transport. An increase in the number of rail passengers and, at the same time, a drop in the number of road transport passengers is consistent with the concept of sustainable development. The purpose of the article is to analyse the preferences of rail and bus passengers and use research results to enhance sustainable development. In order to achieve this aim, the method of critical analysis of available secondary research results and the survey method were adopted, with the use of a questionnaire in primary research. The author’s own research was conducted on a representative sample of 331 young passengers. On the basis of available secondary research results, the price, travel time and modern technology categories as well as elements thereof were selected for analysis. The study results may be used to formulate a strategy for sustainable development of transport, contributing to the reduction of road passenger transport in favour of rail transport.

Analyzing multi-factor effects on travel well-being, including non-linear relationship and interaction

ABSTRACT Enhancing the travel well-being of commuters is crucial for the sustainable development of urban transportation and requires a clear understanding of the factors. However, existing research on the factors affecting travel well-being has not considered travel disturbance. This research adds travel disturbance and effort to a survey in Ningbo, China. Using this dataset, machine learning algorithms were employed to explore the complex relationship of seven variables on commuters’ travel well-being. The results demonstrated machine learning algorithms such as Gradient Boosting Decision Tree and Random Forest outperform traditional linear regressions in analyzing travel well-being. The study identified built environment (Relative Importance = 24.6%) and affective effort (Relative Importance = 17.2%) were key determinants of travel well-being. Non-linear relationship between key variables and travel well-being was also investigated, and revealing a complex interaction between these variables. This research could help transportation managers provide more targeted and efficient suggestions to increase urban commuters’ travel well-being.

METHODOLOGY FOR ASSESSING THE LEVEL OF A TRANSPORT ENTERPRISE SUSTAINABLE DEVELOPMENT

The goal of this article is to develop a methodology for assessing the level of sustainable development of a transport enterprise, which allows to supplement and expand the system of coefficients, taking into account the specificity of initial and boundary conditions of functioning, as well as the nature of the enterprise's goals, which makes it possible to adapt to a dynamically changing environment. To achieve this goal, a number of modern general scientific methods and research techniques have been used, namely: abstract and logical, including analysis and synthesis, induction and deduction; generalisation – for reviewing information sources, studying local and foreign experience; system analysis – for a holistic perception of the research object and a comprehensive analysis of the relationship between the elements within the defined problem as a whole; problem-oriented – for scientific substantiation of the methodology for assessing the level of transport sustainable development.
 Modern economic trends make it possible to emphasise the theoretical and practical importance of the problem of increasing the efficiency and sustainability of transport enterprises on the basis of technological transformation. At the same time, sustainable development of transport will entail technical and technological progress of the economy as a whole.
 The paper considers a methodology for assessing the level of sustainable development of transport enterprises, which involves five stages. The study also developed an approximate goal-setting system, which can be edited by the enterprise in accordance with its own priorities. This study systematised the indicators of sustainable development, which were divided into two groups, qualitative and quantitative, based on the goals set. Also, the article proposes a general integral indicator for assessing the level of sustainable development of an enterprise, based on the target approach, within which the indicators for achieving which are divided into indicators for achieving qualitative and quantitative goals in the areas of economic, environmental, social and technological activities, which allows to assess the degree of their implementation.
 The theoretical conclusions, approaches and recommendations proposed in the article can be used to determine the level of sustainable development of a transport enterprise, on the basis of which it is possible to formulate a conclusion about its ability to carry out further activities, which will allow making the right management decisions.

Autonomous vehicle market development in Beijing: A system dynamics approach

A system dynamics (SD) model for the autonomous vehicles (AVs) market development in Beijing is proposed. The model approaches the vehicle scale evolution with the marketization development of private AVs and shared AVs. Some potential factors such as trust, AV purchase willingness, AV using willingness and shared AV service accessibility, are analyzed. Based on the passenger vehicle situation in Beijing, optimistic scenarios from 2014 to 2050 are developed. The base scenario involves the marketization of private AVs and the operation of shared AV fleets, and based on the levels of driving automation, which are divided into six types. The causal feedback relationship and system flow diagram are illustrated. Results show that with the introduction of AVs in Beijing, the number of private vehicles is significantly decreased, which is dependent on the use of shared AVs. To compare with the private vehicle ownership in 2020, the total number of private vehicles has decreased and the number of the private vehicles is over 2.2 million vehicles in 2050. After 2030, the shared vehicle fleet will be dominated by the high-level shared AV and the number of high-level shared AVs is about 2 million. Further, to consider the impact of ride-sharing, the model compares the different attitudes for customers to share their rides and use the shared AV alternative ratio to approach this. The result shows that the extreme ratio will reduce the number of shared AVs, and the fleet size of shared vehicle is about 400,000 vehicles in 2050. For the low ratio scenario, the fleet size of shared vehicle will increase a lot to over 3,186,000 vehicles, which will lead to a large number of cars on the road and thus increase congestion. The introduction of AVs is expected to reduce the number of private vehicles; However, the uncertainty of residents' attitudes towards car sharing will affect the introduction of AVs. At present, the existing policies prefer to limit the number of vehicles by controlling car registration in Beijing. In the future, with the application of AVs, this could be adjusted by encouraging ride sharing, to achieve sustainable urban transport development in Beijing.

Economic and air pollution disparities: Insights from transportation infrastructure expansion

We explore the regional disparities in economic and health benefits from the expansion of Japan’s high-speed railways and highways over 35 years. Utilizing market access and instrumental variables strategies, we establish a causal relationship between transportation expansion and its economic and health consequences, the latter of which are driven by air quality outcomes. Nationally, over 35 years, transportation expansion has significantly reduced the suspended particulate matter density by 2.96% and increased income by 15.80%. However, these benefits are largely concentrated in developed regions such as Tokyo, leaving other cities with only slight improvements in SPM reduction and income growth. Our estimates suggest the 35-year transportation expansions is estimated to have provided $817.60 and $4,701.20 per capita health and economic benefits, respectively. We discuss the transformation of the industry structures driving these changes. The asymmetrical benefits distribution poses challenges, emphasizing the necessity of addressing these disparities for future sustainable transportation development.

Impact of Port Shallowness (Clearance under the Ship’s Keel) on Shipping Safety, Energy Consumption and Sustainability of Green Ports

In a majority of ports, a ship’s speed is limited for reasons of navigational safety. At the same time, captains and port pilots choose the speed of the ship, but it cannot be higher than the speed allowed in the port. Therefore, the speed of the ship also depends on the experience of the masters and harbor pilots and the sailing conditions in specific situations. Choosing the optimal speed of the ship in the port, considering the hydrodynamic effect of shallow water and the controllability of the ship, can help reduce fuel consumption and ship emissions, which is important for the development of a sustainable port. In all cases, the safety of the shipping is the highest priority. The main objectives of this article are determining the optimal speed of ships in ports with low clearance under a ship’s hull, ensuring navigational safety, reducing fuel consumption and emissions, and creating a sustainable port. This article presents the methodology for calculating the optimal ship speed as the minimum controllable speed, fuel consumption and emission reduction, as well as its implications for sustainable and green maritime transport and port development. The methodology presented has been tested on real ships and using a calibrated simulator, navigating through port channels and port water’s restricted conditions.

Analysis of the sustainable public transportation plans in Poland

A sustainable transportation development plan is a strategic document that is created to guarantee convenient conditions in terms of the mobility of users and to ensure all other aspects that aim to improve the quality of life in the city. It is created on the basis of existing planning practices, using documents that already exist in this area and with the participation of various social groups. For this reason, the purpose of this study is to analyze sustainable public transportation development plans for selected 10 municipalities in Poland. The authors will analyze the sustainable development plans of these cities, try to find common features in them, and suggest how a given plan can be expanded to seek better solutions for creating sustainable urban mobility to replace previously developed transportation plans.

Development of micromodels of traffic flows, taking into account environmental factors

The article considers an actual problem of organizing a safe and sustainable urban transport system. We have examined the existing positive global experience in both infrastructural and managerial decisions. Then to assess possible solutions at the stage of infrastructure design, we have developed the simulation micromodels of transport network sections of the medium-sized city (Naberezhnye Chelny) with a rectangular building type. The models make it possible to determine the optimal parameters of the traffic flow, under which pollutant emissions from cars would not lead to high concentrations of pollutants. Also, the model allows to obtain the calculated values of the volume of emissions of pollutants and the parameters of the traffic flow (speed, time of passage of the section, etc.). On specific examples, the proposed method’s effectiveness is shown. Case studies of cities of different sizes and layouts are implementation examples and possible uses proposed by the models. This study has shown the rationality of the suggested solution at the stage of assessing infrastructure projects and choosing the best option for sustainable transport development. The proposed research method is universal and can be applied in any city.

Lithium-Ion Battery State-of-Health Prediction for New-Energy Electric Vehicles Based on Random Forest Improved Model

The lithium-ion battery (LIB) has become the primary power source for new-energy electric vehicles, and accurately predicting the state-of-health (SOH) of LIBs is of crucial significance for ensuring the stable operation of electric vehicles and the sustainable development of green transportation. We collected multiple sets of charge–discharge cycle experimental data for LiFePO4 LIB and employed several traditional machine learning models to predict the SOH of LIBs. It was found that the RF model yielded relatively superior predictive results, confirming the feasibility of applying the RF model to SOH prediction for the electric vehicle LIB. Building upon this foundation, further research was conducted on the RF improved model for LIB SOH prediction. The PSO algorithm was employed to adaptively optimize five major parameters of the RF model: max_depth, n_estimators, max_features, min_samples_split, and min_samples_leaf. This adaptation addresses the issue of prediction errors that stem from human experience to optimize parameters in the RF model. The results indicate that the RF improved model proposed in this paper can further improve the prediction accuracy of LIB SOH. Its model evaluation index also outperform others, demonstrating the effectiveness of this approach in the management of LIB SOH for new-energy electric vehicles. This contributes significantly to urban environmental protection and the development of green transportation.

Quantifying Road Transport Resilience to Emergencies: Evidence from China

Facing the shock of emergencies, how resilient is the road transport system? In this process, how are the system’s absorption capacity, adaptability, and recovery capacity? These are very important for the development of sustainable road transportation. Taking China’s road transport during the COVID-19 pandemic as the research object, this paper introduces an integrated resilience quantification method, draws a road transport resilience curve, and comprehensively and dynamically analyzes and compares the resilience of China’s road transport system at different stages among different regions and under different epidemic waves. The results show that the resilience of road passenger and freight transport differs in the face of external disturbance. Freight transport resilience is better than that of passenger transport. Compared to passenger transport, freight transport is more robust; the impacted speed is slower, the recovery speed is faster, the recovery capacity is stronger, and the affected period is shorter. There is regional heterogeneity in road transport resilience. This heterogeneity is reflected in the whole change process of system performance with external disturbance, including absorption capacity, adaptation capacity, and recovery capacity. The resilience of road transport under different waves of the epidemic is different. Compared to the first wave of the epidemic, the resilience of road transport indicators at all stages has been dramatically improved in the later rebound wave of the epidemic. This can help in the development of evidence-based road transport sustainability strategies.

A structural equation modeling framework for studying sustainable freight transportation indicators in emerging economies

The movement of commodities in emerging economies is largely facilitated by freight transit. The major obstacle to developing sustainable freight transportation systems in emerging economies are multiple dynamic uncertainties and inherent sustainability risks. This study determines the major indicators responsible for the sustainability of freight transportation. Initially, 16 Sustainable Transportation Indicators (STIs) are identified through literature and discussed with experts under five sustainability parameters: reputation, overall service quality, resilience, economic model, and job satisfaction. The identified STIs are categorized under the economic, social, environmental, and risk categories. Later, a hypothetical conceptual Structural Equation Model (SEM) is employed to analyze and verify the data. The results from the study show that STIs such as Reputation, Employment Benefits, and Infrastructure and Technology are crucial for the development of sustainable freight transport in emerging economies as they can enhance the efficiency and productivity of transportation systems and, hence their importance must be considered for future deployment of freight transportation in these economies.

Villagers' travel burden and the built environment in rural China: Evidence from a national level survey

Travel burden on rural residents is an important theme in transport geography. However, the empirical evidence for this remains scarce. This paper aims to shed light on rural travel burden by examining the relationship between the rural built environment and villagers' travel burden, as measured by the time and money spent on essential and regional trips. A national survey of rural residents in 287 villages across China is analysed. The results show that residents living in rural areas are more likely to be faced with travel burden than are urban residents when accessing livelihood opportunities in local rural settlements and regional urban centres. The built environment attributes are significantly correlated with residents' travel burden. Specifically, the distance from the village to the destination has the strongest relationship with essential trips compared with other built environment variables. Villagers tend to incur higher time costs for an essential or regional trip when paved roads, bus stations and high-quality roads are less accessible. Bus transfer times from the village to the town centre, the population density, and the accessibility of local facilities also show significantly correlation with villagers' travel cost. Moreover, those residents who are elderly, low-income, or have a physical disability are more likely to suffer from high travel burden. The findings will enhance our understanding of the role of land use and transport policies in releasing villagers' travel burden to achieve sustainable transport development in rural contexts.

The Construction of Seaports in the Arctic: Prospects and Environmental Consequences

The Arctic zone of the Russian Federation is of strategic importance for the country. Considering the fragility of Arctic ecosystems, special attention needs to be paid to the sustainable development of transport and related infrastructure within the framework of the “blue economy” concept, which is relevant for Arctic waters. At the same time, it is necessary to identify the main factors and tasks of creating transport and port infrastructure, building a modern fleet, and organizing fisheries and tourism in an environmentally sound manner. The purpose of the study is to consider the problems of anthropogenic influence for seaport facilities and to create a conceptual model of an environmental risk management system. The existing problems of Arctic ports and infrastructure are analyzed and existing business processes are considered, taking into account the peculiarities of their functioning in Arctic conditions. To systematize environmental assessments and establish dependencies between the main indicators describing the impact of port activities on elements of the natural environment, ontological domain engineering is proposed. It systematizes the basic terminology used within different subject areas of ecology and risks and allows one to visualize the relationships between elements of the natural environment, objects, port systems, their parameters and impact factors to assess the impact of the seaport on the natural environment. The results of ontological engineering (design and development of ontologies) in the field of risk management are presented. Future research will be aimed at developing the applied aspect of applying the results of ontological engineering in terms of specific engineering studies related to the assessment of anthropogenic load on the Arctic territory using simulation modeling.

Transformer vehicle re-identification of intelligent transportation system under carbon neutral target

Vehicle re-identification technology plays a pivotal role in intelligent transportation systems, contributing significantly to improved traffic scheduling and reduced net-zero emissions. It holds immense potential for advancing carbon neutrality efforts. By accurately recognizing and tracking vehicles, this technology optimizes traffic flow, enhances energy efficiency, reduces carbon emissions, and fosters sustainable transportation development. However, prevailing CNN-based feature extraction methods often lack the capability to associate global features, while Transformer-based approaches tend to overlook crucial local feature differences. Effectively mining local features and integrating them with global features are critical aspects of successful vehicle re-identification techniques. To tackle this challenge, we present a novel approach, the Locally Significant Feature Rearrangement (LSFR) module, based on the Swin Transformer model. This module enhances the learning of local features by initially focusing on specific regions using a single-shot multi-box detector (SSD) and employing an adaptive attention learning mechanism to highlight fine-grained local features. Subsequently, the salient local features are rearranged to prioritize their importance, and their embedding layers are fused with global features in a recombined manner. Our experimental results on the VeRi-776 and VehicleID benchmark datasets validate the effectiveness of our proposed method as a reliable technique to support intelligent transportation systems and drive progress towards traffic carbon neutralization.