Green Transportation Research Articles

Hybrid data mining and data-driven algorithms for a green logistics transportation network in the post-COVID era: A case study in the USA

This study examines the problem of item allocation in a post-COVID environment with various products and a large customer base. The number of customers has increased due to the rise of internet access and the growing willingness to shop online. Problems such as the timely delivery of goods or services, the selection and destination of orders in decentralized warehouses, and the allocation of warehouses to customers are difficult to overcome with a large variety of items and many customers. It has been proposed that mathematical modeling in combination with meta-heuristic solution techniques solve these problems. However, solving mathematical models is very time-consuming and labor-intensive because there are many different location situations. Due to computing power and memory capacity advances, researchers have been looking at data-driven solutions to these problems. This study aims to tackle the diversity of commodities and the number of consumers in the post-COVID era by proposing a hybrid data-driven approach that combines data mining and mathematical modeling to solve mathematical location models with high accuracy in less time. This paper was implemented based on data from real cases in the USA.

Does green transportation affect carbon emission efficiency? Evidence from a quasi-experimental study in China

The establishment of a low-carbon transportation system (LCTS) holds prominent importance in advancing modern transportation development and achieving green growth. Employing the LCTS pilot policy as a shock to green transportation construction in China, we investigate its influence on carbon emission efficiency (CEE) using urban panel data from 2006 to 2021. Results based on difference-in-differences (DID) show that LCTS contributes to increasing CEE following such a pilot policy. This finding still holds after we perform a propensity score matching DID method, double machine learning, instrumental variable method, heterogeneous treatment effect, and other robustness checks. Meanwhile, the mediation analysis shows that the increased CEE can be accounted for by spurring green innovation activities. Moreover, the moderation outcomes reveal that FinTech exerts a positive moderating influence on the increased impacts of LCTS on CEE. Heterogeneity analysis shows that LCTS's impact on CEE varies by region and development level. Overall, our research stresses the importance of green transportation construction in shaping CEE, which has significant practical and theoretical implications for scholars and policymakers.

Does built environment improvement promote transport equity for internal migrants in Beijing?

Numerous studies and practices leverage improvements in the built environment to encourage green transportation due to its significant potential to shape travel behaviors. Yet, the equity impacts of these improvements on vulnerable populations remain underexplored. This study seeks to address the question: whether built environment improvement strategies advance transport equity? Using a travel survey from Beijing and combining the Capability Approach with the Random Parameter Logit model, we develop a multilevel discrete choice model to estimate capability changes for four hypothetical scenarios of built environment improvement and conduct transportation equity analysis using Maximax principle. Our results show that increasing the mix of land use is prioritized to enhance commuting equity for carless internal migrants. Expanding bus route coverage is recommended to alleviate commuting inequality for low-income internal migrants. However, increasing road density or decreasing the distance to the nearest metro station may not effectively mitigate commuting inequities for disadvantaged internal migrants.

Carbon emission characteristics and carbon reduction analysis of employee travel-taking a research institute as an example

This paper adopts the “baseline scenario method” to construct a comprehensive model for calculating and reducing carbon emissions generated by employee travel, including the accounting of carbon emissions from commuting and business travel, as well as the assessment of green travel for carbon reduction. The study employs methods such as questionnaires and on-site interviews to collect travel data from employees of a research institute in Beijing as a case study. The results show that employees’ commuting methods are diverse, with the subway being the primary mode of travel; however, business travel generates higher carbon emissions, particularly among employees with higher education levels. The research concludes that the model proposed in this paper provides a framework for preliminary carbon emission estimation, but to improve the accuracy of the estimates, more variables and factors need to be considered, and the limitations of the model are pointed out. The research findings have significant implications for policy and institutional practices, suggesting the adoption of more targeted measures to reduce the use of high-carbon-emission travel methods and to encourage the use of green travel options. With the continuous advancement of data collection technologies in the future, it will be possible to further establish a more refined carbon emission accounting model and obtain more accurate and comprehensive travel data, thereby providing solid data support for the development of more effective carbon reduction strategies and policies.

Is green transportation efficiency the panacea for alleviating carbon lock-in? The case of China

The development of green transportation is crucial for creating a low-carbon roadmap in the transportation sector. We calculate the efficiency of green transportation in China and then examine its effect on carbon lock-in. The asymmetric nexus between green transportation efficiency and carbon lock-in is investigated, and the moderating and mediating effects are also examined. Our results indicate that (1) green transportation efficiency is effective in reducing carbon lock-in and promoting a low-carbon transition; (2) The relationship between green transportation efficiency and carbon lock-in is asymmetric, with green transportation efficiency having a stronger effect in areas with lower levels of carbon lock-in. (3) Environmental regulation can contribute to the eradication of carbon lock-in and strengthen the effect of green transportation efficiency, showing significant a moderating effect. (4) Green transportation efficiency indirectly affects carbon lock-in by promoting energy consumption efficiency and renewable energy development.

Hierarchical nested riblet surface for higher drag reduction in turbulent boundary layer

Riblets can be potentially employed to passively reduce the turbulent friction drag. However, the drag reduction performance of riblets does not currently meet expectations, which could assist in emission reduction and energy conservation in green transportation. This study proposes and validates a topological form of hierarchical nested riblets (HNR) that significantly enhances the drag reduction performance. To explore the drag reduction enhancement mechanism, direct numerical simulations are performed for flow simulation on the riblet surface under different Reynolds numbers. The results show that under the riblet dimensionless spacing of the riblet s+≈21, the drag reduction performance of the HNR surface improves by about 70% compared to that of the uniform riblet surface, which is inspired by shark skin. From the perspective of turbulence statistics, the HNR surface reduces the turbulent mixing near the wall, weakening the momentum transfer. Furthermore, the transient flow field shows that the secondary riblet in HNR prevents some turbulent flow and streamwise vortices from entering the groove, considerably weakening the dispersive stress induced by the secondary flow. Moreover, owing to the influence of the secondary riblet, small-scale turbulence develops and strengthens into large-scale turbulent motion, which is advantageous to the boundary layer flow and results in drag reduction improvement.

Influence of urban functional zone change on land surface temperature using multi-source geospatial data: A case study in Nanjing City, China

The urban heat island effect is a prevalent urban concern, and studies on its influencing factors are essential to mitigate its negative effects and promote sustainable urban development. Although many studies have revealed the impact of land cover change on land surface temperature (LST) during urbanization, most have focused only on built-up areas without considering the relationship between urban internal functional structure and LST. To clarify the influence of changes in urban functional zones (UFZs) on LST, focusing on the downtown area of Nanjing City, China, this study proposed an effective framework using multi-source geospatial data for qualitative and quantitative analysis. Specifically, very high spatial resolution images and point of interest data were jointly used to generate UFZ maps using an advanced deep learning approach, and LST distribution maps were retrieved from Landsat 8 images using the radiative transfer equation. The UFZ and LST maps were then overlaid and analyzed to reveal the impact of UFZ change on LST. The results showed that in 2013, 2018, and 2022, the residential region constituted the largest proportion of area, comprising 23.52%, 24.52%, and 27.28%, respectively. The areas of unused region and transport region experienced the most rapid decrease and increase of 6.08% and 4.05% from 2013 to 2022, respectively. Furthermore, the area of sub-high temperature zone decreased the most, by 3.47%, whereas that of the high-temperature zone increased the most, by 6.05%. In the study area, water and green space maintained relatively low LSTs, whereas residential region and unused region exhibited higher LSTs. From 2013 to 2022, UFZ changes contributed to a 0.71°C increase in LST. Transfers from green space, water, commercial region, transport region, and industrial region mostly resulted in a higher LST, which was associated with a decrease in fractional vegetation cover (FVC). Transfers from unused region, residential region, and public service region mostly contributed to reducing LST, which was caused by the increase in FVC. The findings and the proposed framework can provide reliable references for urban managers to optimize urban spatial layout and promote sustainable urban development.

Large-scale energy storage for carbon neutrality: thermal energy storage for electrical vehicles

AbstractThermal Energy Storage (TES) systems are pivotal in advancing net-zero energy transitions, particularly in the energy sector, which is a major contributor to climate change due to carbon emissions. In electrical vehicles (EVs), TES systems enhance battery performance and regulate cabin temperatures, thus improving energy efficiency and extending vehicle range. The enhanced efficiency reduces overall energy consumption in EVs. Consequently, this reduction in energy demand can lead to decreased infrastructure needs, minimising the scale and investment required in energy production and distribution systems. Furthermore, the integration of TES with existing infrastructure allows for the simultaneous charging of thermal and electrical energy, leveraging waste heat or renewable energy sources. This not only cuts costs by optimizing resource use but also bolsters sustainability by minimising reliance on non-renewable energy sources. The widespread adoption of TES in EVs could transform these vehicles into nodes within large-scale, distributed energy storage systems, thus supporting smart grid operations and enhancing energy security. Strategic investments and regulatory updates are essential to realise a sustainable, carbon-neutral transportation future, underpinned by robust, cost-efficient infrastructure.

Influence factors on travel mode preference of working residents living far away from downtown area on workdays: A hybrid method integrating random parameter logit model and Apriori algorithm

This study presents a detailed analysis on the characteristics of travel mode preference of working residents living far away from downtown area on workdays, using GPS-based activity travel diary data from Shangdi area (Beijing). A hybrid method integrating random parameter logit model with systematic heterogeneity (RPL-SH) and Apriori algorithm is put forward to explore the influence factors and interaction effects affecting travel mode preference. First, the RPL-SH model is established to explore significant factors, and capture the unobserved random heterogeneity and systematic heterogeneity due to individual characteristics on the travel mode preference. Then, these significant factors are used to generate association rules by Apriori algorithm to investigate statistical associations between the specific travel mode preference and these significant factors. Ten significant factors are found in the RPL-SH model, in which annual household income is normally distributed. The results of the Apriori algorithm indicate that some factors combined with other factors could significantly influence working residents’ travel mode preference. For example, the combination of lower annual household income and shorter distance between workplace and the nearest bus stop is highly associated with green travel mode preference. Moreover, the results show that the proposed hybrid method not only demonstrates the consistency of the results of the two methods, but also plays a complementary role in exploring more information on travel mode preference. This research hopes to give regulators a better understanding on how working residents living far away from downtown area choose their travel mode, so as to develop more effective and targeted measures for reducing private car use and alleviating workday traffic congestion.

Research on the Location Selection Problem of Electric Bicycle Battery Exchange Cabinets Based on an Improved Immune Algorithm

The rise of new energy technologies has accelerated progress towards sustainable development, and many companies are beginning to invest in renewable resource-related facilities. Electric bicycles have always been an important mode of green transportation; however, they also have problems such as slow charging, difficult charging, and that burning and short circuiting may occur during charging. Electric bicycle battery exchange cabinets effectively solve these problems by exchanging low batteries with full batteries instead of charging. However, current battery exchange cabinets face the problems of insufficient construction and unreasonable site selection. Therefore, this paper proposes a location selection model for electric bicycle battery exchange cabinets based on point demand theory, aiming to maximize rider satisfaction and the service capacity of exchange cabinets. The immune algorithm is introduced to solve the location model; however, the traditional immune algorithm has some problems such as poor stability and slow convergence. In this paper, the mutation process of the traditional immune algorithm is improved by introducing multi-point mutation, guided mutation, and local search. Finally, based on the data of electric bicycle riders in Shanghai, we verify that the location model based on point demand theory performs well on two objective functions of rider satisfaction and battery exchange cabinet service capability. We also expand the application of point demand theory to location models. Then, by conducting experiments with different parameter groups, through sensitivity analysis and convergence analysis, we verified that the improved immune algorithm performs better than the traditional immune algorithm in its accuracy, search accuracy, stability, and convergence.

Electrolytes for High-Safety Lithium-Ion Batteries at Low Temperature: A Review.

As the core of modern energy technology, lithium-ion batteries (LIBs) have been widely integrated into many key areas, especially in the automotive industry, particularly represented by electric vehicles (EVs). The spread of LIBs has contributed to the sustainable development of societies, especially in the promotion of green transportation. However, the high demand for battery performance and safety in these fields has made the high viscosity, volatility, and potential leakage inherent in traditional organic liquid electrolytes a constraint on their further expansion. Especially at low temperature, the increased viscosity of the electrolyte, reduced solubility of lithium salts, crystallization or solidification of the electrolyte, increased resistance to charge transfer due to interfacial by-products, and short-circuiting due to the growth of anode lithium dendrites all affect the performance and safety of LIBs. Therefore, improving the safety performance of LIBs under low-temperature environments has become a focus of current research. This paper primarily reviews the progress made in utilizing different types of electrolytes in LIBs to enhance safety and optimize low temperature performance and discusses the current research progress as well as the future development direction of the field.

Green commuting within the x-minute city: Towards a systematic evaluation of its feasibility

In cities, carbon emissions associated with commuting transport is large and significant. This study integrates data about the jobs-housing relationship, road network configurations, public transport availability, and real-time traffic conditions during peak hours to evaluate the commuting feasibility and performance of green travel modes (walking, cycling and public transport) and explore the potential determining factors. In the context of the x-minute city, the green travel commuting feasibility (GTCF) indicator measures the percentage of the working population who can commute via green travel modes within specific x-minute thresholds. 15, 30, 45 and 60 min have been considered. In comparison, the car travel commuting feasibility (CTCF) indicator is developed to evaluate the corresponding commuting performance by car. Nanshan district of Shenzhen in China is taken as a case study. Results show that distinct gaps exist between GTCF and CTCF. Public transport performs well only for long-distance (> 8 km) commuting trips, and cycling does well for short (< 3 km) and medium-distance trips. Geographically, areas with large differences of GTCF and CTCF are identified for improving green travel modes with priority. Potential factors influencing GTCF are explored with a regression model and case-based analysis. Smaller street blocks, bus route realignment and better jobs-housing balance should be targeted. Designing cycling short-cuts and public transport routes that avoid traffic jams are also recommended to promote green commuting. The findings demonstrate that real-time trip-planning information is of great value in evaluating the commuting feasibility of multimodal travel and identifying influential factors for achieving the x-minute city.

Green architecture in tourism sustainable development a case study at Laweyan, Indonesia

ABSTRACT The degradation of local culture is often a consequence of tourist kampung development. However, Laweyan stands out as an example where a tourist village was developed while successfully preserving both the environment and local culture. The research aims to formulate a strategy that promotes a green environment by exploring the potential characteristics of local cultural heritage and emphasizing sustainable preservation. By utilizing an exploratory descriptive method and analyzing the potential and characteristics of the area, the study identified several strategies for developing cultural heritage areas in tourism kampung. These strategies include promoting green communities, establishing green open spaces and infrastructure, implementing green waste management, adopting green transportation, prioritizing green water practices, incorporating green building techniques, and utilizing green energy sources. The implementation of green architecture is one of the key factors for success in sustainable village development. The concept of green architecture involves integrating building design and the environment with the aim of maintaining a balance between quality development and environmental preservation. The successful implementation of these strategies relies on a collaborative social approach that raises awareness and encourages active participation from both the community and the government in preserving the authenticity of the local culture.

Optimizing green solid transportation with carbon cap and trade: a multi-objective two-stage approach in a type-2 Pythagorean fuzzy context

Optimizing green solid transportation with carbon cap and trade: a multi-objective two-stage approach in a type-2 Pythagorean fuzzy context

Design of urban low-carbon green transportation demonstration area in the context of "dual carbon" --Taking Wuhua District of Kunming City (Zhengyi Road and Sanshi Street area) as an example

In the context of "dual-carbon", by reconstructing the relationship between people and vehicles, optimizing spatial quality, and taking street space renovation as a starting point, we can continuously improve the travel experience of human-centered neighborhoods, build a higher-quality living environment, and guide green travel. Under this context, this study takes Wuhua District, Kunming, Zhengyi Road and Sanshi Street as a case to explore the design of urban low-carbon green transportation demonstration area under the background of "dual-carbon". By analyzing the "dual-carbon" strategy and related policies, and taking into account the current transportation situation in Wuhua District, Kunming, it is found that there are problems such as traffic congestion, chaotic parking, and poor bus routes in this area. To address these challenges, this study proposes a series of optimization measures based on successful cases at home and abroad, including improving the transportation network, strengthening non-motorized parking management, introducing intelligent traffic management systems, and optimizing the connection between bus routes and rail transit. These measures will help improve transportation efficiency, reduce congestion, promote green travel, and provide useful lessons and references for the construction of low-carbon transportation demonstration zones in other cities.

The links between sustainability dimensions and green campus initiatives in mountain universities

Sustainability and green campus initiatives are widely examined in developed countries but less attention has been paid in developing countries such as Pakistan. Therefore, this study intends to examine the links between sustainability dimensions and green campus initiatives by mediating role of teachers and students’ involvement. Green campus or sustainable campus or environment friendly campus is based on the principles of environmental sustainability, incorporating social, and economic and environmental dimensions. Questionnaire for assessment of sustainability was adopted and 529 responses were received from the faculty, management and servicing staff of the seven Mountain Universities of the Gilgit Baltistan and Azad Jammu and Kashmir in Northern Pakistan. Partial Least Square Structural Equation Modeling (PL-SEM) was used to analyse the data. The results indicated that energy conservation, water conservation, green transport, sustainable waste management have enhanced campus green initiatives. Teachers and students’ involvement partially mediate the relationship between green transport strategies, sustainable waste management and green campuses initiatives. While on another hand, teachers and students’ involvement have not mediated the links between energy conservation, water conservation and green campus initiatives. The study contributes to theory building in the area of green and environment friendly campus initiatives by enriching the understanding of the processes carrying the effect of sustainability dimensions and both teachers and students’ involvement.

Comparative Analysis of Countries in Terms of Sustainable and Green Transportation Using Multi-Criteria Decision Making Approach

Comparative Analysis of Countries in Terms of Sustainable and Green Transportation Using Multi-Criteria Decision Making Approach

Technology for Green Hydrogen Production: Desk Analysis

The use of green hydrogen as a high-energy fuel of the future may be an opportunity to balance the unstable energy system, which still relies on renewable energy sources. This work is a comprehensive review of recent advancements in green hydrogen production. This review outlines the current energy consumption trends. It presents the tasks and challenges of the hydrogen economy towards green hydrogen, including production, purification, transportation, storage, and conversion into electricity. This work presents the main types of water electrolyzers: alkaline electrolyzers, proton exchange membrane electrolyzers, solid oxide electrolyzers, and anion exchange membrane electrolyzers. Despite the higher production costs of green hydrogen compared to grey hydrogen, this review suggests that as renewable energy technologies become cheaper and more efficient, the cost of green hydrogen is expected to decrease. The review highlights the need for cost-effective and efficient electrode materials for large-scale applications. It concludes by comparing the operating parameters and cost considerations of the different electrolyzer technologies. It sets targets for 2050 to improve the efficiency, durability, and scalability of electrolyzers. The review underscores the importance of ongoing research and development to address the limitations of current electrolyzer technology and to make green hydrogen production more competitive with fossil fuels.

A Path Planning Method Based on Hybrid Sand Cat Swarm Optimization Algorithm of Green Multimodal Transportation

Aiming at the difficulty of measuring various costs and time-consuming elements in multimodal transport, this paper constructs a green vehicle comprehensive multimodal transport model which incorporates transportation, transit, quality damage, fuel consumption, and carbon emission costs and proposes a hybrid embedded time window to calculate the time penalty cost in order to reflect the actual transport characteristics. Furthermore, in order to better solve the model, a hybrid sand cat swarm optimization (HSCSO) algorithm is proposed by introducing Logistic–Tent chaotic mapping and an adaptive lens opposition-based learning strategy to enhance the global search capability, and inspired by the swarm intelligence scheme, a momentum–bellicose strategy and an equilibrium crossover pool are introduced to improve the search efficiency and convergence ability. Through testing nine benchmark functions, the HSCSO algorithm exhibits superior convergence accuracy and speed in dealing with complex multi-dimensional problems. Based on the excellent global performance, the HSCSO algorithm was utilized for multimodal vehicle transportation in East China, and a path with a lower comprehensive cost was successfully planned, which proved the effectiveness of the HSCSO algorithm in green intermodal transport path planning.

The Challenges in Adopting Electric Buses: A Case from Melaka, Malaysia

The Malaysian government has initiated a collaboration with private agencies to expand the green transport ecosystem by introducing electric buses. Despite these efforts, the adoption of electric buses in urban areas remains minimal. This paper addresses two research objectives: (a) to identify the challenges in adopting electric buses, and (b) to recommend improvements for adopting electric buses in Malaysia. Utilizing a qualitative methodology, this study aims to capture the experiences and reflections of interviewees through targeted population or place studies. This approach allows for the collection of detailed information and the development of new concepts and theories. The interviews revealed three main barriers to adopting electric buses in Melaka: battery reliability and durability, a lack of charging infrastructure, and insufficient operational knowledge. The paper suggests that the government and policymakers should take proactive measures to promote green technology and increase the acceptance of electric buses in urban areas through awareness campaigns.