Shared E-scooter (SE) travel is a low-carbon transportation method that can be further enhanced by integrating with metro systems. This study aims to quantify the impact of the built environment, attitude preferences, weather perception, and other factors on the evaluation and intention to use the \"SE-metro transfer\" travel mode, as well as how to efficiently and concisely measure and model these effects. Empirical analysis was conducted using questionnaire data from Changsha, China, with 683 participants surveyed. Three satisfaction models were established and compared based on the Technology Acceptance Model (TAM), and an optimal M2 model was expanded to incorporate users\' subjective perceptions of weather, proposing a method to simplify questionnaire length. The study found that well-designed vehicles and infrastructure, along with necessary supporting facilities, play important roles in enhancing SE usage. However, there are still many areas for optimization in Changsha\'s SE policies. Despite the advantages of SE in terrain and physical fitness, which have significantly expanded and changed their user base compared to traditional shared bicycles, there is still much potential to adapt to the middle-aged and older user groups. The results of this study can provide valuable insights for professionals and government officials in designing systems, constructing infrastructure, and formulating policies.

The construction of road infrastructure has resulted in the degradation of wildlife habitat and the decrease of ecological network connectivity and stability. Studying the impacts of road infrastructure on wildlife life and migration is significant for regional wildlife conservation and ecological network optimization. We assessed the impacts of road infrastructure on habitat suitability using the MaxEnt model based on wildlife occurrence point data in the Guangdong-Hong Kong-Macao Greater Bay Area. We constructed the ecological networks and identified ecological breakpoints using the minimum cumulative resistance model, and compared the ecological network connectivity of different scenarios with the landscape connectivity index and graph theory index. The results showed that railway and motorway significantly affected habitat suitability, causing a decrease in wildlife habitat suitability. Affected by road infrastructure, the fragmentation of ecological sources intensified, the resistance of ecological corridors increased, and the ecological network connectivity and stability significantly decreased. A total of 536 ecological breakpoints were identified, which were concentrated in the area adjacent to ecological sources. The results would provide important scientific references for wildlife habitat conservation and ecological restoration in the Guangdong-Hong Kong-Macao Greater Bay Area.
道路基础设施的建设导致野生动物栖息地生境退化,以及生态网络连通性和稳定性降低等问题。研究道路基础设施对野生动物生活和迁徙的影响,对区域野生动物保护和生态网络优化具有重要意义。本研究基于野生动物的出现点位数据,利用MaxEnt模型评估粤港澳大湾区道路基础设施对生境适宜性的影响,采用最小累计阻力模型构建生态网络并识别生态断裂点,同时,使用景观连通性指数与图论指数对比不同情景的生态网络连通性。结果表明: 研究区内部的铁路和高速公路对生境适宜性产生显著影响,造成野生动物栖息地适宜性降低;受道路基础设施的影响,生态源地破碎化加剧,生态廊道的通行阻力增加,生态网络的连通性和稳定性明显下降;共识别生态断裂点536处,集中分布于生态源地附近。研究结果可为粤港澳大湾区野生动物栖息地保护和生态网络连通性修复提供重要的科学参考。.

A reasonable land use development around subway stations can balance the utilization rates of the subway system during peak and off-peak hours, thereby enhancing its service levels and operational efficiency. Analyzing the temporal distribution patterns of passenger flow and their influencing factors is crucial for determining the optimum ratio of each land use type surrounding metro stations. Thus, this paper employs principal component analysis (PCA) at first to investigate the temporal distribution of metro ridership, and identify their main patterns and factor loadings. Then, using geographically weighted regression, the study examines the spatial dependencies between the main component proportions and influencing factors, focusing on Xi\'an subway stations. The results indicate that the temporal distribution of passenger flow can be decomposed into three principal components: the first representing commuting characteristics, and the second and third representing regulating functions. The overall distribution is a composite of these components in varying proportions. Residential and educational land uses primarily drive morning and evening peak flows, with residential land use in the city center and peripheral areas having a more pronounced effect compared to transitional areas. Conversely, commercial & office, healthcare, and recreational & park land mitigate peak flows and increase off-peak flows. External hub enhances passenger flow throughout the day, while industrial land use has negligible impact.

The widespread application of pesticides in China has led to the accumulation of residues in soil. However, few regional studies have fully elucidated the characteristics of pesticide residues in soil (PRS) and the associated risks to the ecosystem and human health on a national level. Therefore, this study aims to compile a dataset on PRS in China from 2006 to 2020 and analyze the interactions and impacts between PRS and the environment. The average concentration of PRS in China was 243.96 μg/kg which was lower than the levels reported in Euro-Americans and other nations. This study revealed PRS in China predominantly originates from organochlorine pesticide residues, with DDTs and HCHs being significant contributors. Despite the high intensity of pesticide application in the Southeast China, PRS concentrations were comparable to those in the Northeast, due to environmental factors that favor pesticide degradation in the Southeast. Both legacy and in-use pesticides were transported by surface runoff or air current, resulting in their accumulation in soil of the lower Yangtze River basin or the piedmont soil of Qinling Mountains, respectively. The average soil environment carrying capacity of PRS in China was -69.5 kg. The ecological risk contributed by PRS in China was mainly at a negligible level. Carcinogenic risks of PRS to adults (4.6 ×10-4) and children (6 ×10-4) exceeded the tolerable thresholds (10-5) by a small margin.

Rapid urbanization has led to the development of intelligent transport in China. As active safety technology evolves, the integration of autonomous active safety systems is receiving increasing attention to enable the transition from functional to all-weather intelligent driving. In this process of transformation, the goal of automobile development becomes clear: autonomous vehicles. According to the Report on Development Forecast and Strategic Investment Planning Analysis of China\'s autonomous vehicle industry, at present, the development scale of China\'s intelligent autonomous vehicles has exceeded market expectations. Considering limited research on utilizing autonomous vehicles to meet the needs of urban transportation (transporting passengers), this study investigates how autonomous vehicles affect traffic demand in specific areas, using traffic modeling. It examines how different penetration rates of autonomous vehicles in various scenarios impact the efficiency of road networks with constant traffic demand. In addition, this study also predicts future changes in commuter traffic demand in selected regions using a constructed NL model. The results aim to simulate the delivery of autonomous vehicles to meet the transportation needs of the region.

The design of transportation networks is generally performed on the basis of the division of a metropolitan region into communities. With the combination of the scale, population density, and travel characteristics of each community, the transportation routes and stations can be more precisely determined to meet the travel demand of residents within each of the communities as well as the transportation links among communities. To accurately divide urban communities, the original word vector sampling method is improved on the classic Deepwalk model, proposing a Random Walk (RW) algorithm in which the sampling is modified with the generalized travel cost and improved logit model. Urban spatial community detection is realized with the K-means algorithm, building the F-Deepwalk model. Using the basic road network as an example, the experimental results show that the Deepwalk model, which considers the generalized travel cost of residents, has a higher profile coefficient, and the performance of the model improves with the reduction of random walk length. At the same time, taking the Shijiazhuang urban rail transit network as an example, the accuracy of the model is further verified.

Bacterial biofilms, especially those formed by pathogens, have been increasingly impacting human health. Bacterial extracellular vesicle (bEV), a kind of spherical membranous structure released by bacteria, has not only been reported to be a component of the biofilm matrix but also plays a non-negligible role in the biofilm life cycle. Nevertheless, a comprehensive overview of the bEVs functions in biofilms remains elusive. In this review, we summarize the biogenesis and distinctive features characterizing bEVs, and consolidate the current literature on their functions and proposed mechanisms in the biofilm life cycle. Furthermore, we emphasize the formidable challenges associated with vesicle interference in biofilm treatments. The primary objective of this review is to raise awareness regarding the functions of bEVs in the biofilm life cycle and lay the groundwork for the development of novel therapeutic strategies to control or even eliminate bacterial biofilms.

This study employs a regression discontinuity design to systematically examine the governance effect of bike-sharing on urban traffic congestion, utilizing city-level data from Beijing, Shanghai, and Wuhan in China between 2016 and 2018. We discover that the introduction of bike-sharing services significantly mitigates traffic congestion in the short term. Our heterogeneity analysis reveals that the initial deployment of shared bicycles primarily alleviates urban congestion, while additional deployments have a limited impact. Further, mechanism test analysis demonstrates that bike-sharing leads to increased metro ridership in these cities, effectively explaining the reduction in road congestion. This study underscores the pivotal role of bike-sharing services in easing urban traffic congestion and provides vital policy insights for enhancing traffic management strategies in Chinese cities.

The Belt and Road Initiative (BRI) stands as the most ambitious infrastructure project in history, marked by its scale of investment, extensive geographical reach across continents and countries, and a diverse array of projects from roads to digital networks. While the BRI\'s environmental sustainability has raised concerns, the impacts of construction materials used in these projects have been overlooked, especially in developing countries. Here, we map and account for the materials embodied in the BRI by integrating, for the first time, official governmental project reports, geographical information, and material flow analysis. We pinpoint and analyze the BRI material stocks in each individual project by material types, countries, regions, and sectors. Between 2008 and 2023, 328 million tons of construction materials have accumulated in 540 BRI projects around the world, mostly in Asia and Africa. Aggregates (sand and gravel) constitute the largest share (82%), followed by cement, steel, and other materials. Most of the materials are used in transportation infrastructure. Our work further highlights some limitations in terms of data quality for such sustainability assessments. By shedding light on the significant impact of BRI projects on raw material usage across the globe, this study sets the stage for further investigations into environmental impacts of BRI and material stock-flow-nexus from perspective of an initiative.

While atmospheric microplastics are known to be transported over long distances, their residence times and transport processes lack clarity. This study utilized natural radionuclides 7Be, 210Pb, and 210Po to explore the transport of atmospheric microplastics in Tianjin, a coastal city in Northern China. Microplastic concentrations ranged from 0.03 to 0.13 particles m-3 over the course of a year. The proportion of microplastic fragments in winter was significantly higher than that in other seasons, with median microplastic sizes in autumn and winter being larger than those in spring and summer. The atmospheric microplastic surface was rough, exhibiting irregular pores and multiple depressions and cracks. Microplastics experienced vertical mixing with the upper atmosphere in April and August and were influenced by rainfall in July. The residence time of atmospheric particles ranged from 9.47 to 22.85 days throughout the year, with an average of 14.41 days. The peak residence time of atmospheric particulates in November may be correlated with increased 210Po levels from coal consumption. Their prolonged atmospheric presence and rough surface allow microplastics to act as carriers for various chemical pollutants, underscoring the complexity and potential risks associated with their presence in the atmosphere.