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In the current context of sustainable development in China, the inherent clean and rapid characteristics of high-speed rail (HSR) are reshaping both economic and green development patterns. From the perspective of HSR network centrality, this study employs a panel dataset encompassing 278 Chinese cities and constructs various difference-in-differences (DID) models to analyze the green innovation effects of the HSR network. Empirical findings indicate that the HSR network significantly stimulates urban green innovation, a conclusion further validated through robustness checks. The mechanism analysis reveals that the HSR network promotes the development of tourism economies along its route and the specialized agglomeration of producer service industries, which, in turn, enhances urban green innovation. Further analysis shows that the extent of this impact is influenced by various heterogeneous characteristics, such as urban size, tourism attributes, resource endowments, environmental institutional foundations, and the characteristics of different urban agglomerations. Additionally, the HSR network boosts green innovation levels in both local and neighboring regions, with the positive spatial spillover effect mainly occurring within 200 km. Our findings provide recommendations for promoting urban green innovation and optimizing the HSR network layout. Furthermore, this study enriches the literature on the environmental and economic effects of the HSR network. • The high-speed rail (HSR) network facilitates green innovation. • We explore tourism economic development and producer service industries agglomeration. • These are crucial pathways through which the HSR network affects green innovation. • The HSR network has spatial spillover effects on green innovation. • The distance of the spatial spillover boundary is investigated. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic significantly affected the global air transport industry, but it also provided a business opportunity for the air freight sector. Many countries, including China, increased the use of all-cargo flights to compensate for the loss of belly capacity. This paper provides a deeper understanding of the Chinese international scheduled freighter network (CISFN) during and post-COVID-19. The results show that the CISFN adapted rapidly to the increasing air cargo volume and continued to expand. The focus of the network expansion has been on developing the hub-and-spoke (H&S) system, which is the most efficient model for accommodating the increase in dedicated cargo demand, rather than establishing point-to-point routes among existing communities. The densification of the H&S system provided more alternatives for the hub cities, and consequently the robustness of the system has improved. Government policies have played a crucial role in shaping China's dedicated air cargo networks. The introduction of some key policies has boosted cargo airline expansion and enhanced the resilience of this sector during the pandemic. However, the network remained vulnerable to disruptions, particularly at some key hubs. • This paper investigates Chinese international scheduled freighter network (CISFN) during and post-COVID-19. • The CISFN adapted rapidly to the increasing air cargo volume and continued to expand. • The network expansion centers around the hub-and-spoke system. • Government policies have played a crucial role in shaping China's air cargo networks. • The network remained vulnerable to disruptions, particularly at some key hubs. [ABSTRACT FROM AUTHOR]

Bicycles play a crucial role in promoting resilient urban mobility, yet current approaches often focus primarily on engineering resilience, emphasising short-term resistance, adaptability, and recovery from disruptions. This perspective tends to overlook the equally important social dynamics and institutional factors. Socio-ecological resilience theory fills this gap by viewing disruptions as opportunities for renewal, innovation, and transformation, recognising that systems operate in dynamic, non-equilibrium states where change is inevitable and unpredictable. However, its application in transport studies has been limited due to the complexity of empirical implementation. This paper utilises the Multi-Level Perspective (MLP) to offer a framework for understanding transport systems as complex socio-technical networks—encompassing artifacts, infrastructure, human actors, regulations, and cultural meanings. MLP's nested, layered ontology helps conceptualise the complexity and evolution of transport systems. Using Hong Kong's dockless bike-sharing system during the social movements and pandemic, this study explores how individual, community, and organisational resilience interact across scales. It shows how institutions both shape and are shaped by human agency, with interpretive flexibility allowing individuals to adapt institutional rules to personal contexts. The structuration of parking practices—shaped by voluntary digital communities managing bike parking and formalised through organisational and regulatory frameworks—illustrates how multi-level resilience arises through interactions among diverse actors, rather than from the mere accumulation of individual actions. While higher degrees of structuration, shaped by the scale of fields and number of actors reproducing them, foster stability, they can also perpetuate social exclusion, highlighting the need for equitable policies that balance individual responsibility with inclusive institutional strategies. • Advances the theoretical understanding of multi-level resilience in socio-technical transport systems. • Contextualises socio-ecological and Multi-Level Perspective (MLP) for transport resilience analysis. • Considers agency-structure dynamics between individual, community, organisational levels. • Examines the dynamic levels of structuration of regime and niche fields and contribution to resilience. • Institutionalisation, while necessary for resilience, can also reinforce social inequalities. [ABSTRACT FROM AUTHOR]

Walking is a cornerstone of urban mobility in Latin America. Therefore, policies that improve pedestrians' perception of the built environment are crucial for policymakers and researchers alike. This paper investigates the influence of built environment factors on perceptions of safety and comfort, as well as pedestrians' preferences for sidewalk characteristics in two Colombian cities: Barranquilla and Santa Marta. For this purpose, we designed a novel survey that combines a choice experiment using real images of residential and commercial areas with a set of perception indicators to estimate hybrid choice models. The study's findings have significant practical implications for urban planning and policy development. In the commercial sector, sidewalk width is the most relevant attribute, followed by obstacles and, to a lesser extent, the presence of pedestrians. In residential sectors, the attractiveness of the environment, the presence of pedestrians, the condition of the sidewalk, and the existence of obstacles are highly relevant in explaining pedestrian demand behavior. The hybrid model indicates that sidewalk width and the presence of obstacles impact the perception of comfort and safety in both sectors. On the other hand, the presence of pedestrians has a positive effect on safety but a negative effect on comfort. These results show that physical attributes of the built environment influence pedestrian perceptions. Improvements in pedestrian infrastructure and the building environment are necessary to encourage walking as an active mode of transportation. They include promoting mixed land use, widening sidewalks, removing obstacles, and maintaining them to ensure continuity and good condition. • More pedestrians' presence enhances safety perception but reduces the perception of comfort. • Obstacles negatively impact pedestrians' perceptions of safety and comfort in commercial and residential areas. • In commercial areas, sidewalk width is relevant to pedestrians' comfort perception. • In residential areas, attractive built environments and well-maintained sidewalks are crucial to increase walking demand. [ABSTRACT FROM AUTHOR]

The high-speed rail (HSR) unites various cities, potentially expanding the production and consumption scale, and improving the efficiency of supply and demand adaptation while fostering increased consumption in local areas. This study investigates the effect of HSR on residents' consumption using data from 260 prefecture-level Chinese cities spanning 2005 to 2021 and discovers the underlying mechanisms through the perspective of innovation factor agglomeration. The findings revealed that the HSR enhanced the clustering of regional innovation factors, thereby stimulating consumption through mechanisms including job conception and product innovation. Further analysis explored that the agglomeration of capital, talent, and data innovation factors driven by HSR development exerted varying degrees of influence on boosting consumption. Furthermore, based on city type and grade, the effect of the HSR on residents' consumption displayed heterogeneity. The findings of the current study carry significant policy implications, suggesting the requirement for tailored planning of HSR development that considers city types and the unique characteristics of various elements, thereby prompting the potential energy of innovation factor agglomeration. [ABSTRACT FROM AUTHOR]

This paper addresses a significant gap in the literature regarding freight trip generation in Large Freight Trip Generators (LFTGs) in urban areas and emerging countries. We employ a comprehensive approach using linear and nonlinear models and Ordinary Least Squares (OLS) techniques to provide insights into various types of urban generators, including universities, firms, shopping centers, and markets. Our research aims to enhance the understanding of trip generation patterns in these diverse LFTG contexts within a framework of modeling and application in public policies. The freight trip generation models were estimated by analyzing the variables associated with the production and attraction of freight trips in an LFTG. The variables used were specific to the type of establishment, such as the number of employees, the area and extent of the commercial premises, hotels, and universities, and the number of rooms and students, respectively. The 2018 Freight Transportation Study of the Medellin Metropolitan Area (Colombia) played a crucial role in our research, providing the data necessary to estimate 108 models explaining freight trip generation in large facilities across seven categories: universities, hotels, firms, shopping centers, hospitals, buildings, and markets. The results can aid in planning LFTG infrastructure in cities, facilitate vehicle emission analysis, and support decision-making by considering multiple methods for planning, making informed decisions, and opening avenues for further research. Additionally, indicators can be created to align with urban norms in city plans; for example, this research proposes an indicator for the urban planning of LFTGs in cities, which can be continuously measured and evaluated alongside the analysis of Traffic Analysis Zones (TAZ). This study is the first in South America and opens the door to logistical planning within Latin American cities for LFTGs. • The paper aims to model freight trip generation (FTG) for large traffic urban generators (LFTGs) in cities of emerging countries. • The study utilizes data from a 2018 freight study in Medellin to estimate 108 models explaining FTG of large facilities. • Simple linear models performed better than multiple regression models in terms of t-Student, Fisher's F, and R-squared values. • The models provide a tool to assess FTG from LFTGs and develop strategies for efficient freight transportation management. • The findings offer insights into urban freight policies in emerging countries undergoing urban growth and planning changes. [ABSTRACT FROM AUTHOR]

In the context of frequent uncertainty risks in the international environment, ports play an increasingly important role in regional export growth. This paper innovatively examines the impact of port shipping connectivity on urban exports from the perspective of microeconomic entities participating in international and domestic circulations. By employing theoretical mechanisms and econometric models, this study explores the impact, channels, moderating effects, and heterogeneity of port shipping connectivity on urban exports. The empirical analysis is based on panel data from 33 ports and 144 hinterland cities in China, covering the period from 2007 to 2021. The findings indicate that improvements in port shipping connectivity drive urban export growth. Domestic and international circulations serve as the channels. Furthermore, the impact of port shipping connectivity on urban exports varies depending on several factors, including production capacity, customs clearance costs, development periods, hinterland types, regional distribution, port ranking, and city ranking. Our research provides policy implications for both central and local governments in China. In summary, local governments, supported and guided by the central government, should promote healthy competition among ports and strengthen coordination between ports and cities. ● The microeconomic effects of port shipping connectivity on urban exports are studied ● Heterogeneity and moderation effect analysis have considered micro-level disparities ● Domestic and international circulations serve as channel mechanisms ● Theoretical model incorporates Hotelling model and value-added decomposition model [ABSTRACT FROM AUTHOR]

Principles of dense, mixed-use environments and pedestrianisation are influential in urban planning practice worldwide. A key outcome espoused by these principles is generating "urban vitality", the continuous use of street sidewalk infrastructure throughout the day, to promote safety, economic viability and attractiveness of city neighbourhoods. Vitality is hypothesised to arise from a nearby mixture of primary uses, short blocks, density of buildings and population and a diversity in the age and condition of surrounding buildings. To investigate this claim, we use a novel dataset of 2.1 million time-lapsed day and night images at 145 representative locations throughout the city of Accra, Ghana. We developed a measure of urban vitality for each location based on the coefficient of variation in pedestrian volume over time in our images, obtained from counts of people identified using object detection. We also construct measures of "generators of diversity": mixed-use intensity, building, block and population density, as well as diversity in the age of buildings, using data that are available across multiple cities and perform bivariate and multivariate regressions of our urban vitality measure against variables representing generators of diversity to test the latter's association with vitality. We find that two or more unique kinds of amenities accessible within a five-minute walk from a given location, as well as the density of buildings (of varying ages and conditions) and short blocks, are associated with more even footfall throughout the day. Our analysis also indicates some potential negative trade-offs from dense and mixed-use neighbourhoods, such as being associated with more continuous road traffic throughout the day. Our methodological approach is scalable and adaptable to different modes of image data capture and can be widely adopted in other cities worldwide. [ABSTRACT FROM AUTHOR]

The intercity multi-transportation networks (MTN), facilitated by aviation and high-speed rail, transcends distance constraints on factor flows, significantly enhancing enterprises' total factor productivity (TFP). This study empirically examines the impact of MTN centrality on enterprises' TFP using a panel dataset ("city-firm") of Chinese A-share listed enterprises from 2010 to 2020. This study reveals several key findings: Firstly, increased MTN centrality markedly boosts enterprises' TFP levels. Secondly, these networks enhance enterprises' TFP by strengthening knowledge spillovers, adjusting industrial structures and achieving economies of scale through intercity connections via aviation and high-speed rail. However, knowledge spillover enhancement and industrial structure adjustment play a more prominent role in advancing the technological progress of enterprises, while economies of scale primarily contribute to improving technological efficiency. Thirdly, the impact of MTN centrality on enterprises' TFP varies across space and time. Core cities experience more pronounced improvements compared to peripheral cities. Overall, the study underscores the positive impact of intercity MTN, supported by infrastructure like high-speed rail and aviation, on micro-enterprises and their internal mechanisms. • Developing the intercity MTN based on the fourth-order tensor model. • Explore the impact of intercity MTN on enterprises' TFP using "city-enterprise" data. • The centrality of cities within MTN significantly enhances enterprises' TFP. • Knowledge spillovers and restructuring industrial serves as mediating mechanisms. [ABSTRACT FROM AUTHOR]

Ride-hailing services (especially motorcycle-based ride-hailing services -MBRH) have seen a boom in Vietnamese cities because these services can serve as a more efficient alternative to urban mobility. However, relatively little is known about travel patterns of sub-population groups of ride-hailing services, including the spatiotemporal demand, origin, and destination patterns of ride-hailing users, and the effects of transit investment on the mode switching from current ride-hailing users. This information is particularly important for the implementation of traffic management measures focusing on public transport, in light of concerns about the reverse side of the ride-hailing services, such as aggravating the traffic conditions and causing losses in the public transport market. In this paper, we present an in-depth analysis of the travel patterns of MBRH, based on large-scale household survey data collected in Ho Chi Minh City, Vietnam, with the statistical technique of Chi-square and Kruskal-Wallis tests. In addition, the independent and combined effects of Revealed Preference (RP) and Stated Preference (SP) data on the mode switch for MBRH users were studied using the Nested Logit models. The results indicate that speed and flexibility are seen as outstanding features of MBRH in attracting users. Furthermore, mode switch model estimation results show that traditional attributes (i.e., travel time and cost) and transit design factors (i.e., accessibility) are of lower importance to mode-switching behavior compared with sociodemographic factors. These findings suggest that MBRH services fill an important transportation niche and may affect the environment and transportation equity. • Motorcycle-based ride-hailing (MBRH) services are prevalent in Vietnamese cities and other cities in Asian countries. • We explore trends in MBRH use, including spatiotemporal travel patterns, trip types, and the benefits of MBRH services among sub-population groups. • We investigated the effects of new transit investment strategies on mode switching behavior targeting MBRH users. • The study contributes to the understanding of MBRH's relative importance in urban mobility. [ABSTRACT FROM AUTHOR]

This paper investigates the welfare costs of urban traffic by considering its implications on consumer retail prices. Using retail price data for 40 goods and services from 70 cities (covering 47 countries) for multiple years, the estimation results suggest that the elasticity of retail prices with respect to the time spent in urban traffic is about 0.5. This elasticity is further connected to the welfare of consumers by using the implications of an economic model. The corresponding investigation shows that reducing the time spent in urban traffic by one minute improves consumer welfare by about 1.3% for the average city, with a range between 0.8% and 2.3% across cities. Several policy suggestions follow regarding how to reduce the time spent in urban traffic that would improve consumer welfare. • Urban traffic increases consumer retail prices. • Urban traffic reduces consumer welfare. • Policies reducing the time spent in traffic would improve consumer welfare. [ABSTRACT FROM AUTHOR]

This study presents the key summary of the inaugural report of the WCTRS Global Subway Efficiency Benchmarking Task Force, focusing on evaluating the operating efficiency of subway systems across Asia, Europe, and North America. Given the increasing need for urban transit authorities to balance multiple objectives, such as reducing greenhouse gas emissions and enhancing public health, this benchmarking initiative provides a crucial assessment of their productivity and efficiency of operations. We employed the Variable Input Productivity (VIP) method intelligently computed by the translog multilateral indexing method, chosen over DEA due to its transitive properties and better suitability for policy applications. Our analysis measures the VIP index, specifically examining labor and soft input productivities, to gauge how efficiently subway systems utilize their variable resources. By adjusting for factors beyond management control through regression analysis, we derived Net VIP scores, offering a more accurate comparison across different cities. The results reveal significant variations in efficiency levels, with some cities demonstrating remarkable productivity despite limited resources while others lag behind due to structural and operational challenges. Our findings underscore the importance of targeted policy interventions to enhance the efficiency of urban rail systems. Above all, the WCTRS Task Force members who volunteered their time and effort hope to raise awareness of efficiency and productivity as an important aspect of managing and operating the subways and other city transit systems. • WCTRS Task Force collaborates to raise global awareness on efficient subway and city transit operations. • Study evaluates subway efficiency in Asia, Europe, and NA, stressing urban transit harmony for diverse goals. • VIP method outperforms DEA for detailed productivity assessment in subway systems. • Cities exhibit efficiency variations; some excel despite limited resources, others face operational challenges. • Policy interventions are vital for enhancing rail system efficiency by adjusting for external factors. [ABSTRACT FROM AUTHOR]

The Chinese government has initiated the Transit Metropolis project, aimed at developing a transit-oriented urban transportation system that progressively enhances the utilization of public transit and encourages private car users to shift towards public transit. Using panel data from 221 cities from 2009 to 2018, we employed a multi-period propensity score matching-differences in differences approach to examine the effects of this project on public transit usage and private car ownership. We utilized the status of a city as a coastal city as an instrumental variable for the Transit Metropolis project to conduct an endogeneity test, ultimately finding no evidence of endogeneity. Even when accounting for competitive policies such as the low-carbon city policy, the results remained consistent, confirming the robustness. The findings suggest that the project has effectively increased public transit use without significantly decreasing private car ownership. However, these impacts vary geographically. Specifically, in Eastern region of China, the project significantly enhanced public transit usage, whereas no comparable significant effect was observed in the Central & Western regions. Regarding private car ownership, the project did not have significant effects in either the Eastern, or the Central & Western regions. These insights provide a reference for further implementing Public Transit Priority policies, help enhance the competitiveness of public transit, and promote the development of transit-oriented urban transportation structures. • Multi-period PSM-DID is used to examine the policy implications of the Transit Metropolis project. • The Transit Metropolis project has effectively boosted public transit usage. • The negative effect of the Transit Metropolis project on private car ownership is not significant. • The policy effect of Transit Metropolis project varies geographically. [ABSTRACT FROM AUTHOR]

The escalating problem of air pollution has recently attracted global attention. The use of electric vehicles (EVs) has emerged as a key strategy for mitigating air pollution in the transportation sector. This study uses the difference-in-differences method to examine the influence and underlying mechanisms of China's Electric Vehicle Demonstration and Promotion (EVDP) policy on air pollution. The results indicate that EVDP policy implementation significantly reduces urban air pollution. The EVDP policy is associated with a 3.1% reduction in fine particulate matter (PM 2.5) emissions, which is equivalent to a reduction of 0.28–1.12% in mortality risk and of 175.1 billion yuan in government expenditure on pollution control. The emission reduction effect of the EVDP policy primarily manifests in cities in the southern region and with high electricity availability, exhibiting insensitivity to variations in city size. The EVDP policy reduces urban air pollution through technological innovation and corporate environmental, social, and governance responsibility. Moreover, the reduced air pollution driven by the EVDP policy can potentially mitigate health inequalities across population groups. These findings provide a foundation for advancing energy-saving development and EV demonstration and promotion in China, thereby promoting high-quality green urban development. • This study examines the influence and underlying mechanisms of electric vehicle promotion policy on air pollution in China. • The electric vehicle promotion policy is associated with a 3.1% reduction in fine particulate matter emissions. • The policy's emissions reduction occurs primarily in southern cities and those with high electricity availability. • The policy reduces urban air pollution through technological innovation and corporate ESG practices. • Reduced air pollution from the policy can potentially mitigate health inequalities across population groups. [ABSTRACT FROM AUTHOR]

Extensive spatiotemporal analyses of long-trend surface ozone in the Yangtze River Delta (YRD) region and its meteorology-related and emission-related have not been systematically analyzed. In this study, by using 8-year-long (2015–2022) surface ozone observation data, we attempted to reveal the variation of multiple timescale components using the Kolmogorov–Zurbenko filter, and the effects of meteorology and emissions were quantitatively isolated using multiple linear regression with meteorological variables. The results showed that the short-term, seasonal, and long-term components accounted for daily maximum 8-hr average O 3 (O 3–8 hr) concentration, 46.4%, 45.9%, and 1.0%, respectively. The meteorological impacts account for an average of 71.8% of O 3–8 hr , and the YRD's eastern and northern sections are meteorology-sensitive areas. Based on statistical analysis technology with empirical orthogonal function, the contribution of meteorology, local emission, and transport in the long-term component of O 3–8 hr were 0.21%, 0.12%, and 0.6%, respectively. The spatiotemporal analysis indicated that a distinct decreasing spatial pattern could be observed from coastal cities towards the northwest, influenced by the monsoon and synoptic conditions. The central urban agglomeration north and south of the YRD was particularly susceptible to local pollution. Among the cities studied, Shanghai, Anqing, and Xuancheng, located at similar latitudes, were significantly impacted by atmospheric transmission—the contribution of Shanghai, the maximum accounting for 3.6%. [ABSTRACT FROM AUTHOR]

With the continuous control of anthropogenic emissions, China's air quality has improved significantly in recent years. Given this background, research on how the short-term exposure risks caused by air pollution in China have changed is insufficient. This study utilized hourly concentration data from ground observation stations and the official air quality guidelines of the Ministry of Ecology and Environment of China and the World Health Organization as standards to systematically investigate the spatiotemporal characteristics and short-term exposure risks of air pollution in China from 2015 to 2022. The results indicate that various atmospheric pollutants except for ozone showed a decreasing trend yearly. Nationwide, both single pollutant air pollution days (SAPDs) and multiple pollutant air pollution days (MAPDs) showed varying degrees of reduction within 15 and 25 days, respectively. SAPD was dominated mainly by excessive PM 2.5 and PM 10 pollutants, while MAPD was dominated mainly by excessive pollutant combinations, including PM 2.5 + PM 10 , CO + PM 2.5 + PM 10 , and SO 2 + PM 2.5 + PM 10. As the concentration of atmospheric pollutants decreased, the total excess risk (ER) decreased yearly from 2015 to 2022, but there were significant regional differences. Now, the ER is less than 0.25% in southern China, in the range of 0.25%-0.5% in the North China Plain and some cities in the northeast, and higher than 1% in the northwest. Particulate matter is currently the primary pollutant posing short-term exposure risk in China, especially due to the impact of sandstorm weather. This study indicates that China's atmospheric cleaning action is significantly beneficial for reducing health risks. [ABSTRACT FROM AUTHOR]

Cities can work towards addressing biodiversity conservation, climate adaptation, and social equity goals. Evidence indicates that cities can foster species conservation and human-nature interactions. Yet achieving multifunctional and equitable urban ecosystems requires addressing ecological gaps, enhancing monitoring methods, and engaging communities in sustainable urban planning. The Special Issue " Ecology for future cities" presented in this editorial, aims to contribute to solving existing gaps by investigating key themes shaping the field of urban ecology and emphasizing advancements to understand the social-ecological dynamics in cities. In this editorial paper, we present the seven papers of the special issue, and how they fall within six topics: (1) mapping urban ecosystems; (2) drivers and implications of human-nature interactions; (3) taxonomic coverage and biodiversity structure; (4) ecological transformations; (5) improving the temporal coverage; and (6) how ecology informs urban planning. We also provide future research directions based on these topics. We conclude the editorial with some personal thoughts regarding the two cities where we grew up, which have shaped our relationships to and understanding of urban ecosystems and contribute to motivating our research interests. [ABSTRACT FROM AUTHOR]

Typically, centimeters per second (cm/s) accuracy can be achieved for velocity estimation based on time-differenced positioning, Doppler velocity, and the time-differenced carrier phase approach in open air conditions. However, velocity estimation performance can deteriorate due to non-line-of-sight (NLOS) signals, multipath effects, and other sources of interference in urban areas. We discuss a velocity estimation method based on the RANdom SAmple Consensus (RANSAC) algorithm and a prior dynamic model is proposed. RANSAC is used to isolate the observations affected by NLOS or multipath, while a prior dynamic model is implemented to provide proper velocity constraint. Vehicle kinematic experiments conducted in both open and complex urban environments demonstrate that the velocity accuracy in all three directions can be improved by over 40 % and centimeter-level velocity accuracy can be obtained in open areas. Moreover, the accuracy can be improved by 78.5 %, 78.5 %, and 68.4 % in the north, east, and up directions compared to that obtained by traditional single-point Doppler velocity, and 10.5 cm/s, 11.0 cm/s, and 14.3 cm/s accuracies are achieved in complex urban areas. Moreover, this method is also reasonably applicable to low-cost receivers. [ABSTRACT FROM AUTHOR]

• A nationwide analysis of e-scooter crashes was conducted using an official UK dataset. • E-scooter crashes showed distinctive patterns compared to overall crash data. • Three typologies of crash records were identified through LCA. • Casualty severity in e-scooter crashes were impacted by multiple demographic and environmental factors. Introduction: Electric-powered scooters (E-scooters), as an emerging sustainable micromobility mode, are increasingly popular. However, safety concerns regarding the use of e-scooters are also rising. For example, in 2022, 1,492 casualties resulting from e-scooter-involved crashes were observed in 24 trial areas across the UK. To enhance the understanding of e-scooter riding risks, this study conducted a nationwide crash analysis using a UK dataset. It explores the spatial and environmental contexts of e-scooter crashes and the factors influencing crash severity. Method: A comprehensive approach, including exploratory data analysis, latent class analysis (LCA), chi-square test, and logistic regression model, were employed. Results: Findings revealed distinctive spatiotemporal patterns in e-scooter crashes compared to overall crashes, with a higher incidence in deprived communities. Three crash typologies were identified using LCA: night-time, morning, and information-deficient. Multiple demographical and environmental factors were found to influence crash severity. Conclusions: Compared to overall crash trends, e-scooter crashes are more prevalent in urban areas with high population density and exhibit distinct peak patterns in the afternoon. Night-time crashes in low-light conditions and morning crashes with ample daylight are two significant crash clusters. Factors such as the involvement of riders aged 45 to 65 (Odd Ratio [OR] = 1.76) or > 65 (OR = 3.61), crashes occurring at late night/early morning (OR = 2.29), and rural locations (OR = 1.72) increased e-scooter crash severity compared to their respective reference groups. Moreover, highly deprived communities not only experience a higher number of e-scooter crashes but also contribute to crash severity. Practical Applications : This study underscores the necessity for targeted interventions, such as providing safety campaigns and training programs for older individuals and e-scooter users residing in dense urban areas. It also highlights the need for policies that address inequities, particularly through improved infrastructure and enforcement in lower-income urban areas with more e-scooter crashes. [ABSTRACT FROM AUTHOR]

• Road crashes are a major social problem, with 1.19 million road fatalities per year. • Speeding is the number one cause of road crashes worldwide, especially in cities where pedestrians are highly exposed. • A thorough literature review was conducted and the effectiveness from 30 km/h speed limits was discussed. • Scientific evidence demonstrated that more than 40% lives saved with the introduction of 30 km/h speed limits in cities. • Launching public awareness campaigns and encouraging Public Transport use and active mobility could be proved beneficial. Introduction: Road crashes are a major social problem, resulting in 1.19 million fatalities and over 50 million injuries annually. Speeding is the primary cause of road crashes worldwide, particularly in cities where pedestrians, cyclists, and motorcyclists are especially vulnerable. This paper aims to review and assess the effectiveness of implementing a 30 km/h speed limit. Method: To achieve this objective, a comprehensive literature review was conducted, evaluating the impact of 30 km/h speed limits on safety, emissions, energy consumption, traffic flow, livability, and health. The systematic literature review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: Current scientific evidence indicated that the introduction of 30 km/h speed limits in cities can save over 40% of lives, alongside significant positive effects on the environment, energy consumption and public health, including reduced fuel consumption and increased walking and cycling. Practical Applications: Public awareness campaigns and promoting the use of public transport and active mobility options, such as walking and cycling, could further support the adoption of 30 km/h speed limits in cities. [ABSTRACT FROM AUTHOR]

To investigate the association between ambient coarse particulate matter (PM 2.5 – 10) pollution and risk of acute schizophrenia episodes. A time-stratified case-crossover study with a two-stage analytical approach was conducted to investigate the association between ambient PM 2.5 – 10 pollution and schizophrenia admissions (an indicator for acute schizophrenia episodes) across 259 Chinese cities of prefecture-level or above during 2013–2017. A conditional logistic regression model was constructed to estimate city-specific changes in hospital admissions for schizophrenia associated with per interquartile range (IQR) increase in ambient PM 2.5 – 10 , and the overall associations were obtained by pooling the city-specific associations using the random-effects model. A total of 817,296 schizophrenia admissions were included in the analysis. Per IQR increase (28.43 μg/m3) in PM 2.5 – 10 at lag01 was associated with an increase of 1.66 % (95 % CI: 0.68 %, 2.65 %) in schizophrenia admissions. Compared to concentrations <30 μg/m3, PM 2.5 – 10 concentrations of 30–49 μg/m3 and ≥50 μg/m3 were associated with increases of 2.25 % (95 % CI: 0.73 %%, 3.79 %) and 4.03 % (95 % CI: 1.92 %, 6.18 %) in schizophrenia admissions, respectively. City-level urbanization has the potential to attenuate the association between ambient PM 2.5 – 10 and schizophrenia admissions (P = 0.0002). Our study provides novel evidence for the acute adverse effects of ambient PM 2.5 – 10 on schizophrenia and calls for special attention on the control of high PM 2.5 – 10 pollution in disease prevention. [ABSTRACT FROM AUTHOR]

• ABM development for residential waste sorting to assess urban scenarios. • ABM links TPB with the percentage of properly sorted waste. • The ABM is spatially explicit and evaluates the location of bins. • Distance to recycling facilities improves organic and residual waste sorting. • TPB enriches residential waste sorting modelling. Managing the diverse waste fractions generated by households presents a significant environmental and logistical challenge. One widely adopted solution is waste sorting at the source, where residents are required to separate their waste into designated containers. The success of this strategy depends on the extent of adoption and the behaviour of residents. Waste separation is a complex activity influenced by various interrelated factors. While the Theory of Planned Behaviour (TPB) has been effectively applied to characterise waste-sorting behaviour, it primarily focuses on internal psychological mechanisms, often overlooking environmental factors such as the placement of waste bins or the condition of sorting stations—critical elements for spatial planning. To bridge this gap, this study presents an agent-based model (ABM) that simulates residential waste sorting in urban scenarios, incorporating TPB for the agents' behavioural architecture (residents). Three features distinguish this ABM from previous efforts: (i) Agents in the model are residents and not aggregated households, allowing for a one-to-one integration with TPB; (ii) the ABM bridges the gap between individual waste sorting behaviour extracted by TPB and outcomes quantifiable through waste sorting metrics; and (iii) the ABM is spatially explicit, enabling the exploration of various urban scenarios. The ABM was applied to two urban areas with differing population densities, demonstrating that changes in bin placement impacts sorting behaviour, and proximity to recyclable waste bins influences the correct sorting of residual waste. This study illustrates how modelling the interaction between the urban environment and waste sorting behaviour can reveal the impact of individual residents' actions on overall waste sorting performance. [ABSTRACT FROM AUTHOR]

[Display omitted] • The first known demonstration of the presence of Litomosoides , a bat microfilaria, in bats in an urban landscape. • Bat microfilaria prevalence is higher in tropical forests compared with urban areas in Mexico. • Within urban areas, impervious surfaces harbor bats with higher microfilaria prevalence than the city periphery. • A potential new species of Litomosoides was discovered in bats, mites, and bat-flies. Litomosoides includes filarial nematodes capable of infecting various vertebrate species. While Litomosoides has been extensively studied in rodents, research on its association with bats remains limited. The transmission dynamics of this parasite are complex, involving moving between different invertebrate hosts before reaching the final host. Most investigations concerning microfilariae have concentrated on their morphological characteristics, with scant attention paid to ecological aspects, particularly in human-altered landscapes. This study represents the first known documentation of Litomosoides in bats within an urban environment. It investigates their response to urbanization in their interaction with the synanthropic bat Artibeus jamaicensis and its ectoparasites. The objective was to explore the influence of urban landscapes on Litomosoides prevalence in synanthropic hosts. Blood samples were collected along urban–rural gradients, and parasite presence was confirmed through direct observation in blood smears and PCR. Phylogenetic analysis based on the mitochondrial cytochrome c oxidase subunit 1 gene (COX1), which exhibited robust support values, indicates that the microfilaria found in A. jamaicensis is closely related to Litomosoides chandleri. However, it also suggests the possibility of an unidentified, and therefore potentially new, species within the genus Litomosoides. Additionally, Litomosoides DNA was detected in Periglischrus iheringi (Acari: Spinturnicidae) and in the bat fly Trichobius intermedius collected from the bat. The parasite sequences obtained from these three interacting species exhibited a genetic distance as low as 0.002. The highest prevalences were recorded in forested areas (28.6%) compared with urban areas (21.2%). However, within the urban landscape, prevalence varied from 3.8% to 21.2%, being highest in densely built-up areas. Analysis of the urban landscape suggested that the prevalence of Litomosoides in A. jamaicensis is the result of a multifactorial and synergistic process involving ectoparasite load, host abundance, and the extent of impervious surfaces (NDBI). [ABSTRACT FROM AUTHOR]

This study examines the factors influencing the travel behaviour of Delhi's working population, utilizing retrospective cross-sectional data from 2005 to 2019 collected across four neighbourhoods. The research provides empirical evidence on how travel mode choices have evolved over time in response to changes in the built environment and socioeconomic conditions. GIS-based analysis was conducted to assess the impact of temporal variations in the built environment on travel behaviour. Results reveal a 21% increase in the reliance on private modes of transportation between 2005 and 2019, with the most significant rise observed in 4-wheeler usage. Conversely, bus usage declined by 32%, attributed to various factors including overcrowding, hygiene concerns, and perceived reliability issues. However, in 2019, Connaught Place reported the highest bus usage at 28%, attributed to its high bus stop density, while enhanced metro facilities across the neighbourhoods led to a 20% increase in overall metro ridership. Multinomial logistic regression analysis identified key socioeconomic determinants of travel behaviour, including age, gender, income, vehicle ownership, and commuter attitude. In 2005, two-wheeler preference over buses was primarily driven by vehicle ownership (O.R.: 620.95), gender (O.R.: 4.20), and income (O.R.: 1.28). By 2019, commuter attitude (ProPV) emerged as a significant factor, alongside vehicle ownership (O.R.: 136.72), ProPV (O.R.: 21.41), and income (O.R.: 2.14). A similar trend was observed for car usage, highlighting the increasing influence of commuter behaviour and attitudes on travel choices over time. These findings underscore critical policy implications for the development and enhancement of Delhi's transport system, offering insights that could be applicable to other cities facing similar challenges. [Display omitted] Key Highlights. ⁃ Travel behaviour is complex, differing by region and evolving over time. ⁃Habitual behaviour shapes work travel mode choices in Delhi. ⁃Mixed land use and good transit access boost public transport use. ⁃Safety and comfort are key in car choice for Delhi's workers. ⁃Built environment, socioeconomics, and behaviour influence Delhi's travel modes. ⁃Delhi's transport planning needs balanced infrastructure and behaviour strategies. [ABSTRACT FROM AUTHOR]

[Display omitted] • Developed a comprehensive urban environmental quality (UEQ) index using a multi-dimensional analytical hierarchical process • Identified disparities in environmental quality across Mumbai, with higher EQI in northern and eastern zones. • An increasing trend of very low and low UEQ from 2017 to 2023, indicating a decline in environmental quality. • 13.1% faces low to very low UEQ, with slum populations and population density identified as key causal factors. • The UEQ index offers actionable insights for sustainable urban planning and policy-making, aligning with urban sustainable development. The rapid pace of urbanization globally, with over 55% of the population residing in urban areas and projections indicating two-thirds by 2050, underscores the critical importance of addressing urban environmental quality (UEQ). The financial capital of India, Mumbai, emblematic of intense urbanization, faces escalating environmental challenges stemming from population growth and economic development. This study employs a multidimensional approach, incorporating remote sensing (RS) data, geographic information system (GIS), demographic data, and other primary datasets to construct a comprehensive UEQ index. The UEQ index is characterized by its integration of diverse indicators such as air quality, green spaces, noise levels, and socio-economic factors, providing a holistic assessment of urban environmental health. Utilizing analytical hierarchical process (AHP) for multi-criteria analysis, the study explores spatial patterns of UEQ and identifies causal parameters, emphasizing Mumbai's slum population, population density, and environmental factors. Multi-collinearity analysis reveals potential risks in interpreting the effects of certain variables, specifically air pollution, population density, and socio-economic status. The high correlation between these variables suggests that their individual impacts on UEQ may be difficult to isolate, potentially leading to overestimation or underestimation of their effects. The study explores the spatial patterns of UEQ in Mumbai, identifying significant disparities across different regions. The spatial analysis indicates that central and northern districts suffer from lower environmental quality due to higher pollution levels, limited green spaces, and higher population densities. The spatial pattern of environmental health in Mumbai shows notable disparities, with central wards such as Andheri East, Andheri West, Khar, Dadar, and Chembur consistently experiencing poorer environmental quality due to higher population density and industrial activity, whereas peripheral wards like Borivali and Colaba enjoy better environmental conditions with more green spaces and lower population density; this highlights the evolving nature of environmental health challenges over time. The study emphasizes a concerning trend with 86.9% of the area classified as moderate to very high UEQ, while 13.1% faces low to very low UEQ. Causal parameter priorities underscore the significant influence of slum population and population density. Compared to existing assessment, this study is mainly associated for determining the trend of UEQ and its associated concerns. The study introduces a replicable UEQ assessment methodology with potential applications globally, offering insights for sustainable urban planning, policy formulation, and environmental management. We have created a detailed UEQ index that combines data from multiple time periods and includes trend analysis, offering a more comprehensive and nuanced assessment of urban environments. The research provides a robust foundation for addressing urban challenges and advancing the principles of sustainable development goals (SDGs) related to environmentally sustainable communities. [ABSTRACT FROM AUTHOR]

• Doppler difference between direct and reflected signals reduces multipath effects. • LEO signals exhibit a considerably larger Doppler difference compared to GNSS. • LEO outperforms GNSS in simulations under multipath conditions. • BOC modulation can enhance LEO pseudorange positioning. Low Earth orbit (LEO) satellites have emerged as a promising solution for positioning in environments where traditional Global Navigation Satellite System (GNSS) faces challenges, such as urban canyons. However, the impact of multipath effects on LEO positioning in such urban settings remains unclear. This study investigates the influence of multipath effects on LEO ranging-based positioning, considering signals with binary phase shift keying (BPSK) and binary offset carrier (BOC) modulations. Theoretical analysis reveals that LEO signals exhibit larger Doppler differences between the direct signal and the reflected signal. This characteristic holds particular promise for mitigating multipath effects, especially when utilizing a high frequency carrier. Subsequently, the study assesses the performance of LEO range measurements and positioning under multipath conditions through a simulated LEO constellation. Comparative analyses are conducted with GNSS performance as benchmarks. Additionally, the effectiveness of BOC modulation in enhancing LEO pseudorange positioning accuracy is observed. The results demonstrate that BOC signals can achieve higher ranging and positioning accuracy than BPSK signals. This finding underscores the potential of LEO satellites as reliable alternatives for navigation in challenging urban environments, highlighting the importance of modulation techniques in optimizing positioning performance. [ABSTRACT FROM AUTHOR]

• Significant reduction of EEG semantic categorization response in AD group. • Group difference is maximal at left occipito-temporal and central channels. • High sensitivity of the frequency-tagging EEG approach at the individual level. Combining electroencephalographic (EEG) recording and fast periodic visual stimulation (FPVS) to provide an implicit, objective and sensitive electrophysiological measure of semantic word categorization impairment in Alzheimer's Disease (AD). Twenty-five AD patients and 25 matched elderly healthy controls were tested with a validated FPVS-EEG paradigm in which different written words of the same semantic category (cities) appear at a fixed frequency of 4 words per second (4 Hz) for 70 seconds. Words from a different semantic category (animal) appear every 4 stimuli (i.e., 1 Hz). Frequency domain EEG analysis showed a robust response objectively identified at specific 1 Hz harmonics over the left occipito-temporal cortex for healthy controls, indexing automatic semantic categorization. However, only a negligible response, less than 25 % of healthy controls', was found in AD patients, this response being inversely correlated with the amount of Tau protein in the cerebrospinal fluid. The significant group difference was maximal when including an additional left central region, with only 2.5 min of testing providing a significant group difference. A reduced semantic word categorisation EEG amplitude rapidly differentiates AD patients from healthy controls. FPVS-EEG provides a valuable electrophysiological index of semantic categorization impairment in AD. [ABSTRACT FROM AUTHOR]

Land cover information is indispensable for advancing the United Nations' sustainable development goals, and land cover mapping under a more detailed category system would significantly contribute to economic livelihood tracking and environmental degradation measurement. However, the substantial difficulty in acquiring fine-grained training data makes the implementation of this task particularly challenging. Here, we propose to combine fully labeled source domain and weakly labeled target domain for weakly supervised domain adaptation (WSDA). This is beneficial as the utilization of sparse and coarse weak labels can considerably alleviate the labor required for precise and detailed land cover annotation. Specifically, we introduce the Prototype-based pseudo-label Rectification and Expansion (PRE) approach, which leverages the prototypes (i.e., the class-wise feature centroids) as the bridge to connect sparse labels and global feature distributions. According to the feature distances to the prototypes, the confidence of pseudo-labels predicted in the unlabeled regions of the target domain is assessed. This confidence is then utilized to guide the dynamic expansion and rectification of pseudo-labels. Based on PRE, we carry out high categorical resolution land cover mapping for 10 cities in different regions around the world, severally using PlanetScope, Gaofen-1, and Sentinel-2 satellite images. In the study areas, we achieve cross-sensor, cross-category, and cross-continent WSDA, with the overall accuracy exceeding 80%. The promising results indicate that PRE is capable of reducing the dependency of land cover classification on high-quality annotations, thereby improving label efficiency. We expect our work to enable global fine-grained land cover mapping, which in turn promote Earth observation to provide more precise and thorough information for environmental monitoring. Our data and code will be available publicly at https://zhu-xlab.github.io/PRE-land-cover.html. [ABSTRACT FROM AUTHOR]

Reconstructing urban areas in 3D from satellite raster images has been a long-standing problem for both academical and industrial research. While automatic methods achieving this objective at a Level Of Detail (LOD) 1 are mostly efficient today, producing LOD2 models is still a scientific challenge. In particular, the quality and resolution of satellite data is too low to infer accurately the planar roof sections in 3D by using traditional plane detection algorithms. Existing methods rely upon the exploitation of both strong urban priors that reduce their applicability to a variety of environments and multi-modal data, including some derived 3D products such as Digital Surface Models. In this work, we address this issue with KIBS (Keypoints Inference By Segmentation), a method that detects planar roof sections in 3D from a single-view satellite image. By exploiting large-scale LOD2 databases produced by human operators with efficient neural architectures, we manage to both segment roof sections in images and extract keypoints enclosing these sections in 3D to form 3D-polygons with a low-complexity. The output set of 3D-polygons can be used to reconstruct LOD2 models of buildings when combined with a plane assembly method. While conceptually simple, our method manages to capture roof sections as 3D-polygons with a good accuracy, from a single satellite image only by learning indirect 3D information contained in the image, in particular from the view inclination, the distortion of facades, the building shadows, roof peak and ridge perspective. We demonstrate the potential of KIBS by reconstructing large urban areas in a few minutes, with a Jaccard index for the 2D segmentation of individual roof sections of approximately 80%, and an altimetric error of the reconstructed LOD2 model of less than to 2 meters. [ABSTRACT FROM AUTHOR]

Fixed-section detection methods, with radar and video as representatives, frequently encounter incomplete detection data at controlled intersections because of high construction costs and insufficient maintenance. This results in ineffective signal control strategies. On the other hand, mobile detection methods, represented by floating cars, can perceive both macro and micro spatial-temporal characteristics of traffic flow. However, their current low penetration rate limits their ability to provide sufficient data support for signal control at intersections.To address this issue, this paper proposes an innovative method to obtain more accurate flow rates for each phase at an intersection through simulation approximation of calibrated parameters. This method utilizes the Webster delay theory to quantitatively describe the relationship between phase flow and vehicle delay, allowing for the inverse estimation of flow rates. These estimated flow rates are then refined using the proposed Radial Basis Function (RBF) neural network approximation method to achieve higher accuracy. Comprehensive experimental results demonstrate that the proposed method effectively improves the accuracy of inverse flow data estimation. This enables the effective utilization of low-penetration-rate floating car data (FCD) in signal control at urban intersections. By leveraging this innovative approach, signal control systems can make more informed decisions, leading to smoother traffic flow and improved traffic management in urban areas. [ABSTRACT FROM AUTHOR]

[Display omitted] • Path-dependence lock-ins are intertwined with biowaste valorization development. • Various types of lock-ins can occur at different transition phases and contexts. • Need to balance policy support between mature and radical innovations. • Actor collaboration essential to identify and address path-dependence lock-ins. • Need to address integration of biowaste with other resources and sector-coupling. Achieving sustainable biowaste management is a key challenge for cities worldwide. In this context, biowaste valorization is an indispensable option for managing unavoidable biowaste and reducing the associated methane emissions. Several innovations that enable biowaste valorization are technologically mature. However, their implementation is still limited in most cities around the world. Therefore, it is essential to better understand the different pathways towards implementing biowaste valorization. This paper presents a case-study of two countries at different phases in their transition to biowaste valorization: Sweden as a case at a mature phase and Greece as a case at a formative phase. We apply the Technological Innovation Systems framework to investigate how innovation systems for biowaste valorization develop and associated path-dependencies. Our findings show that various path-dependence lock-ins can occur at different transition phases. Our empirical insights suggest that a focus on the diffusion of certain mature innovations can support the growth of biowaste valorization systems. However, it can also lead to path-dependence lock-ins that influence the systems' resilience to shocks. We thus recommend decision-makers to pursue balance between the rapid diffusion of mature innovations for biowaste valorization and parallel support for experimenting with more radical innovations to harness the systems' resilience to shocks. [ABSTRACT FROM AUTHOR]

• A machine learning model was developed to identify PM 2.5 drivers in various cities. • The Tree-structured Parzen Estimator can enhance model predictive performance. • Socioeconomic and industrial activity are key drivers of PM 2.5 concentrations. • Changing trajectories of factors exacerbating or mitigating PM 2.5 were identified. Reducing urban fine particulate matter (PM 2.5) concentrations is essential for China to achieve the Sustainable Development Goals (SDGs). Identifying the key drivers of PM 2.5 will enable the development of targeted strategies to reduce PM 2.5 levels. This study introduces a machine-learning model that combines CatBoost and the Tree-Structured Parzen Estimator (TPE) to analyze PM 2.5 concentration across 297 cities between 2000 and 2021. SHapley Additive exPlanations (SHAP) were employed to identify the primary factors influencing urban PM 2.5 concentrations. The study revealed that the proposed model has high accuracy in predicting urban PM 2.5 concentrations, achieving a coefficient of determination (R2) score of 96.44%. Socioeconomic and industrial activity are key drivers of PM 2.5 concentrations. This study not only quantifies the primary factors exacerbating or alleviating pollution for each city or province during the 2000–2021 period but also evaluates the influence of operational factors such as technological and public financial expenditures. In 2000, the main contributors to pollution in four heavily polluted cities included substantial nitrogen oxide emissions, inadequate technology investments, and excessive population density and liquefied gas consumption. Due to the rapid reduction in nitrogen oxide emissions, pollution levels in these cities have improved substantially. In the future, the most effective strategies for pollution reduction in these cities will focus on controlling population density and slowing down mining development. The proposed framework serves as a robust evaluation tool and can propose tailored strategies to control PM 2.5 concentrations effectively in each city. [ABSTRACT FROM AUTHOR]

Urbanisation and changes in land use and land cover (LULC) significantly impact Urban Heat Islands (UHI). Despite extensive research on UHI, regional variations demand localised studies. This research assesses the UHI effect in Damascus, Syria, where rapid urbanisation threatens environmental balance. Leveraging Google Earth Engine, Landsat 8, and MODIS data, LULC changes, temperature patterns, NDVI, and NDBI, have been analysed with a focus on the summers of 2013, 2017, and 2022. Results revealed a substantial 12 % increase in urban areas between 2013–2022, accompanied by an 11 % decrease in green spaces. Land surface temperatures (LST) rose from 47.1 °C in 2013 to 48 °C in 2022. NDBI analysis confirmed built-up area expansion, while NDVI indicated dwindling vegetation cover. The pronounced UHI effect (48.7 °C) in industrial and densely populated areas during summer were observed. A strong positive correlation existed between LST and NDBI 90 %, and a moderately negative correlation between LST and NDVI. These findings highlight the adverse impact of urbanisation on Damascus' climate. They underscore the need for urban planning strategies prioritising green space preservation and sustainable development to mitigate the UHI effect and ensure a healthier urban environment. [ABSTRACT FROM AUTHOR]

Innovations around electric vehicle (EV) technology are viewed as a promising pathway to rapidly decarbonise transport systems in transition studies. However, the mobility histories and path dependencies that shape these transitions are spatially uneven both horizontally across different geographies and vertically between different scales of authority and responsibility. As such, they are rooted in the assumptions and power relations that underlay the policy processes of city and metropolitan governance. This study takes the novel approach of comparing these processes both horizontally between cities and vertically between levels of government. The analysis is based on 50 expert interviews with local and national actors involved in delivering policy related to electric mobility in four European cities: Bristol, United Kingdom; Oslo, Norway; Poznań, Poland, and Utrecht, Netherlands. In all four cities, national, inter- and supra-national pressures generate a perception among some interviewees that the transition to electric mobility, and particularly the electrification of private cars, is inevitable. Yet because modal thinking permeates urban transport policymaking, the majority of our experts define sustainable and just urban mobility as that involving modes other than the private car. A key contribution of this study is revealing this tension between national EV priorities and urban aims to reduce car traffic, which subconsciously influences local policymakers' perceptions of the transition to electric mobility. The study also offers new insights into how city and metropolitan policymakers can be more inclusive, innovative, and locally-responsive in shaping policies for accommodating both EVs and new modes like e-scooters. • The processes for making urban electric mobility policy are contextual and uneven. • National governments prioritise the low-carbon transition to electric vehicles. • This transition to electric mobility is seen as inevitable, but inequitable. • Modal thinking conditions perceptions of sustainable, just urban mobility policy. • Cities take various approaches to make electric mobility policy more inclusive. [ABSTRACT FROM AUTHOR]

Port integration (PI) can eradicate homogeneity and disorderly competition, realize the green intensive development of port cities, and is a crucial step in enhancing port competitiveness. This paper builds an assessment framework for green development efficiency (GDE) that takes social welfare, environmental regulation, economic growth into account, and uses the Super-SBM model to calculate the GDE based on panel data from 113 Chinese port cities from 2003 to 2020. Furthermore, the influence of PI on the GDE of port cities and its transmission mechanism is assessed using the PSM-DID model. The results show that the GDE of port cities has a fluctuating upward trend, but the overall level is low, and the social development index (SDI) can effectively improve the efficiency level. PI can significantly improve the urban GDE, and various robust results show that the above conclusions are credible. Heterogeneity analysis reveals that PI contributes more to the GDE of inland port cities than it does to coastal port cities. The GDE of the small-medium sized cities can be greatly enhanced by PI, and the results are better when the "Government driven + market decided" pattern is used. PI encourages technology innovation, which can enhance the urban GDE. Finally, some policy recommendations are made to encourage the excellent development of Chinese port cities. • Proposes a new evaluation system of GDE, including economic growth, environmental regulation and social welfare. • Studies the impact of PI on the GDE of port-cities. • Demonstrates that PI can stimulate the GDE of cities, and its effects grow with time. • Finds that the success of port integration varies per geographical region, integration mode and the size of the city. • Establishes that technological innovation (tech) plays an intermediary role between PI and GDE. [ABSTRACT FROM AUTHOR]

Low-emission zones (LEZs) aim to improve urban air quality and reduce emissions but often face public opposition due to their regressive impacts on accessibility. However, the causes of these regressive impacts remain poorly understood. This study investigates the factors driving inequalities in the impacts of LEZs on job accessibility across occupational categories in eight French cities. Using ex-ante open-source data, it computes expected job accessibility losses due to LEZs per occupational category. Additionally, it provides a counterfactual decomposition of the disparities in LEZs' impacts between six drivers: ownership of polluting vehicles, workers' residences and workplaces within the LEZ, accessibility of workers' homes and workplaces via public transportation, and feasibility of active transportation modes for commuting between homes and workplaces. The findings reveal that LEZs are predominantly regressive in six out of the eight cities examined. Despite a higher concentration of high-income workers and jobs within LEZs, resulting in significant accessibility losses for this group, low-income workers bear a greater burden due to the limited availability of public transportation near their residences and workplaces, longer commutes to work, and higher shares of polluting vehicles. These findings help inform potential complementary policies to address the regressive effects of LEZs. • This paper analyzes Low Emission Zones' (LEZ) impacts on access to jobs in 8 French cities. • LEZs have regressive impacts in 6 out of the 8 cities studied. • It decomposes between 6 key drivers that may explain disparities in LEZ impacts. • Urban forms and polluting vehicle ownership play against unskilled workers. • Policy design plays in favor of unskilled workers. [ABSTRACT FROM AUTHOR]

Internal migrants in China frequently travel between their hometowns and the cities where they work, creating ample opportunities for cross-regional transmission of tuberculosis (TB). The aim of this study was to explore the role of internal migrants in transmitting TB across different regions and the contribution of cross-region transmission to China's TB burden. The study included a total of 8664 patients with TB and their Mycobacterium tuberculosis isolates, collected from two large cities and three rural regions. Genomic clusters were defined as having a genomic distance of ≤12-single nucleotide polymorphisms. Cross-regional clusters were defined as clusters containing patients from at least two regions, indicative of cross-regional transmission. A total of 2403 clustered cases (27.7%) were grouped into 845 clusters, of which 142 (16.8%) were cross-regional. An increased risk for cross-regional transmission was found for internal migrants (adjusted OR (aOR), 1.45; 95% CI, 1.13–1.87), individuals aged <55 years (aOR, 2.73; 95% CI, 1.81–4.13), and housekeepers/factory workers (aOR, 1.16; 95% CI, 0.90–1.50). Among 200 cross-regional transmission events identified by transmission inference, 96 occurred between urban patients, 98 between urban and rural patients, and only six between rural patients. Notably, 93.5% (187/200) of cross-regional transmission events involved internal migrants. Epidemiological data showed that just 5.5% of cross-regional transmission events involved patients from the same township or neighbouring counties, where the transmission likely occurred. The mobility of the internal migrant population appears to be responsible for most cross-regional transmission of TB in China. The magnitude and dynamics of cross-regional transmission should be addressed in future strategies to reduce the incidence of TB in China. [ABSTRACT FROM AUTHOR]

Domiciliary dental care (DDC) is essential for maintaining oral health in disabled and homebound patients who face barriers to accessing dental services. With Taiwan nearing super-aged society status, the demand for DDC is rising. However, comprehensive data on DDC availability and distribution across Taiwan are lacking. Hence, this study aimed to provide a comprehensive overview of the distribution of DDC across Taiwan's districts from 2018 to 2023, and to analyze the estimated ratios of disabled individuals per healthcare provider in each district. Data on DDC-providing hospitals and dental clinics from these years were obtained from government sources. Descriptive statistics quantified DDC facilities distribution and growth. The number of disabled individuals per district was used to estimate ratios of disabled persons to DDC facilities. DDC facilities increased from 47 in 2018 to 98 in 2023. Urban areas showed higher prevalence of DDC services, while some rural and offshore areas had limited or no access. Taichung and Kaohsiung had the highest numbers of DDC providers, while Penghu and Lianjiang had none. Ratios of disabled individuals to DDC facilities varied widely, with Taichung having the lowest ratio and Yunlin and Chiayi the highest. In conclusion, DDC availability in Taiwan has significantly increased, but geographical disparities persist. These findings underscore the need for targeted policies and resource allocation to address gaps in DDC provision, particularly in underserved areas. [ABSTRACT FROM AUTHOR]

Urban areas are growing with the growth in urban population and rapidly transforming the land use land cover (LULC), which is capable of affecting the potential of groundwater recharge at a spatial level. It is essential to recognize the complexities of urban growth along with dynamic and static natural parameters that influence the groundwater recharge in the urban region. No substantial inclusion of Groundwater Recharge Potential Zones (GWRPZ) is evident in contemporary master plans of Indian cities, resulting in a declining trend of groundwater tables with increasing dependency. The study discusses temporal changes in the urban LULC of Ajmer City in the State of Rajasthan in India and its impact on the overall Groundwater Recharge Potential Zone over a duration. Nine physical parameters, geology, lithology, geomorphology, lineament density, slope, drainage density, groundwater table, LULC and Rainfall, are used as thematic layers along with their subclasses. The Multi-criteria Decision Analysis of AHP and Weighted Overlay Analysis in GIS are applied to analyze variations at the spatial level on a temporal basis. In addition, Geostatistical techniques such as Empirical Bayesian Kriging (EBK) and Inverse Distance Weightage (IDW) are also applied to interpolate and analyze the thematic layers of the Groundwater table and Rainfall, respectively. The study delineates and analyzes the spatiotemporal variations in the GWRPZs. The confusion matrix method is also applied for validation and accuracy, which is crucial for rationalizing the water-sensitive physical planning process and instrumental in formulating suitable strategies and guidelines for preserving, managing, and retrofitting the groundwater recharge zones at the urban level in the Indian scenario. [ABSTRACT FROM AUTHOR]

• SPAs were measured in indoor dust collected from 10 provinces in China. • The concentrations of ∑ 6 SPAs in indoor dust were 15.4 to 3210 ng/g dry weight. • The highest concentration of ∑ 6 SPAs was found in Sichuan Province. • Toddlers have the highest risk of exposure to SPAs from dust. Synthetic phenolic antioxidants (SPAs) are widely used in diverse industries due to their exceptional antioxidant characteristics. However, human exposure to SPAs may cause health problems. In this study, 226 dust samples were collected from 10 provinces in China, and six SPAs (three parent SPAs and their three transformation products) were analyzed. The concentrations of ∑ 6 SPAs (the sum of six target compounds) ranged from 15.4 to 3210 ng/g (geometric mean (GM): 169 ng/g). The highest concentration of ∑ 6 SPAs was found in Sichuan Province (GM: 349 ng/g), which was approximately 4 times higher than that in Hubei Province (81.6 ng/g) (p < 0.05). The concentrations of butylated hydroxytoluene (BHT), 2,2′-methylene bis (4-methyl-6‑tert-butylphenol) (AO2246), 2,6-di‑tert‑butyl‑1,4-benzoquinone (BHT-Q), 2,6-di‑tert‑butyl‑4-(hydroxymethyl) phenol (BHT-OH), and ∑ p -SPAs were substantially higher in dust from urban areas than rural areas (p < 0.05). AO2246 concentration in dust from homes (GM: 0.400 ng/g) was about 4 times higher than that in workplaces (0.116 ng/g) (p < 0.01). Significantly higher ∑ p -SPAs concentrations were found in dust from homes (GM: 17.5 ng/g) than workplaces (11.4 ng/g) (p < 0.01). The estimated daily intakes (EDIs) of ∑ 6 SPAs exposed through dust ingestion were 0.582, 0.342, 0.197, 0.076, and 0.080 ng/kg bw/day in different age groups, and exposed through dermal contact was 0.358, 0.252, 0.174, 0.167, and 0.177 ng/kg bw/day. EDIs showed that the exposure risks of SPAs decreased with age. This is the first work to determine SPAs in dust from 10 provinces in China and investigate the spatial distribution of SPAs in those regions. [Display omitted] [ABSTRACT FROM AUTHOR]

To explore the multicenter characteristics of endocrine-like phthalate esters (PAEs) in household dust and propose effective control strategies for global indoor public health. An on-site observational investigation was conducted in nine Chinese cities from 2018 to 2019. A total of 246 household dust samples were collected and analyzed for ten PAE congeners using Gas Chromatography-Mass Spectrometry (GC-MS). Questionnaires were used to gather information on building conditions, indoor behaviors, and ventilation habits. In residential dust from the nine cities, the total concentrations of the ten PAE congeners (∑PAEs) ranged from 0.921 to 29097.297 µg/g. Dicyclohexyl phthalate (DCHP) and di (2-ethylhexyl) phthalate (DEHP) were the dominant congeners in ∑PAEs. Childhood exposure to PAEs through dust ingestion was four orders of magnitude higher than through inhalation, with a carcinogenic risk of 5.47 × 10−6 for DEHP exposure in household dust. Higher ∑PAEs concentrations were associated with higher temperature, double glazing, wall paint usage, television and computer use, and indoor plant growth. This multicenter on-site investigation confirmed PAE pollution characteristics and uncovered the inacceptable risk of daily DEHP exposure in household dust under real living conditions. Effective mitigation measures based on household-related information, residential characteristics, decoration materials, and lifestyle should be taken to build a healthy household environment. [Display omitted] [ABSTRACT FROM AUTHOR]

Majority of carbon emissions originate from fossil energy consumption, thus necessitating calculation and monitoring of carbon emissions from energy consumption. In this study, we utilized energy consumption data from Sichuan Province and Chongqing Municipality for the years 2000 to 2019 to estimate their statistical carbon emissions. We then employed nighttime light data to downscale and infer the spatial distribution of carbon emissions at the county level within the Chengdu-Chongqing urban agglomeration. Furthermore, we analyzed the spatial pattern of carbon emissions at the county level using the coefficient of variation and spatial autocorrelation, and we used the Geographically and Temporally Weighted Regression (GTWR) model to analyze the influencing factors of carbon emissions at this scale. The results of this study are as follows: (1) from 2000 to 2019, the overall carbon emissions in the Chengdu-Chongqing urban agglomeration showed an increasing trend followed by a decrease, with an average annual growth rate of 4.24%. However, in recent years, it has stabilized, and 2012 was the peak year for carbon emissions in the Chengdu-Chongqing urban agglomeration; (2) carbon emissions exhibited significant spatial clustering, with high-high clustering observed in the core urban areas of Chengdu and Chongqing and low-low clustering in the southern counties of the Chengdu-Chongqing urban agglomeration; (3) factors such as GDP, population (Pop), urbanization rate (Ur), and industrialization structure (Ic) all showed a significant influence on carbon emissions; (4) the spatial heterogeneity of each influencing factor was evident. [ABSTRACT FROM AUTHOR]

As cities are faced with increasing resource and environmental problems, sustainable urban growth is progressively becoming dependent on enhancing Green Financial Performance (GFP). Although China's new energy transition program represents an exciting paradigm change in the field of green energy, there needs to be more analysis on its impact on environmentally responsive economic development. This study evaluates the GFP of 255 Chinese cities using the non-radial distance's role approach, using city level panel data from 2005 to 2021. Based on the analysis, the results are then utilized to give quasi-experimental observations about the impact of the New Energy Demonstration City (NEDC) policy on urban GFP. China's NEDC policy has been shown to enhance green economic growth in urban areas, with 2% greater GFP in demonstration cities. This approach promotes sustainability using eco-finance, technology, and industry, although its effects differ depending on geography and available resources. The results remain stable, even after extensive robustness testing. According to a heterogeneity study, GFP of the central and western region, along with non-resource cities are more strongly impacted by the NEDC policy. Analysis of the policy's underlying mechanisms reveals that progress in technical innovation, upgrading industries and development of green finance are the primary forces behind the policy's beneficial effects. The NEDC policy can strike a good balance between environmental and economic nexus, thereby becoming a model for sustainable urban development. • City-level panel data and a non-radial distance method were used. • Evaluate 255 Chinese cities' Green Financial Performance (GFP) from 2005 to 2021. • Urban green economic growth enhanced by New Energy Demonstration City (NEDC). • Green finance, industry advances, and new technology enhance NEDC's success. [ABSTRACT FROM AUTHOR]

• 0.613 kg/cap/d based on sampling of the waste generated in 81 communities. • Average waste composition is 68 % biowaste, 23 % recyclable and 9 % other. • MSW collection frequency is once a week for 40 % of the rural population. • Household biowaste use reduces the amount of waste to be managed by up to 64 %. • Recyclable waste is barely recovered and is centralized in urban areas. Municipal solid waste management is one of the greatest challenges for environmental sustainability and well-being in developing countries, where the infrastructure and financial resources required to carry out such services are often lacking. The design of solutions that adequately respond to local needs must be based on quality information about the quantity and composition of the generated waste and current management practices. This study evaluated domestic waste generation and its management in 81 communities in Ecuador based on sampling at the source and population surveys. An average household waste generation value of 0.613 kg/cap/d was obtained, of which biowaste accounted for 68 % of the total generation, followed by 23 % recyclable material and 9 % other non recyclable waste. Even though some councils have set up differentiated collection systems for inorganic material in urban areas, these systems are still absent in many rural areas, which explains why waste is not separated in 70 % of the studied communities. Furthermore, only 70 % of the rural population in the country has a waste collection service, and waste in some communities is still thrown into water bodies or burned. Rural populations often use biowaste at home by composting it or as animal feed, which are good practices that should be considered in the diagnosis reports and incorporated into waste management planning. [ABSTRACT FROM AUTHOR]

Street-view imagery has been densely covering cities. They provide a close-up perspective of the urban physical environment, allowing a comprehensive perception and understanding of cities. There has been a significant amount of effort to represent the urban physical environment based on street view imagery, and this representation has been utilized to study the relationships between the physical environment, human dynamics, and socioeconomic environments. However, there are two key challenges in representing the urban physical environment of streets based on street-view images for downstream tasks. First, current research mainly focuses on the proportions of visual elements within the scene, neglecting the spatial adjacency between them. Second, the spatial dependency and spatial interaction between streets have not been adequately accounted for. These limitations hinder the effective representation and understanding of urban streets. To address these challenges, we propose a dynamic graph representation framework based on dual spatial semantics. At the intra-street level, we consider the spatial adjacency relationships of visual elements. Our method dynamically parses visual elements within the scene, achieving context-specific representations. At the inter-street level, we construct two spatial weight matrices by integrating the spatial dependency and the spatial interaction relationships. It could account for the hybrid spatial relationships between streets comprehensively, enhancing the model's ability to represent human dynamics and socioeconomic status. Furthermore, aside from these two modules, we also provide a spatial interpretability analysis tool for downstream tasks. A case study of our research framework shows that our method improves vehicle speed and flow estimation by 2.4% and 6.4%, respectively. This not only indicates that street-view imagery provides rich information about urban transportation but also offers a more accurate and reliable data-driven framework for urban studies. The code is available at: (https://github.com/yemanzhongting/HybridGraph). • A framework for street representation with street-view imagery considering multi-level spatial effects • A dynamic weighting module incorporates the spatial adjacency relationships of visual elements at the intra-street level. • A hybrid graph neural network fuses the spatial dependencies graph and spatial interactions graph at the inter-street level. [ABSTRACT FROM AUTHOR]

• Investigating the effect of restrictions on spatiotemporal distribution of crashes. • Employing a logit model to analyze the injury severity of crashes after restrictions. • Significant decrease in number of crashes after restrictions, especially on weekends. • Spread of crashes in the outer city as well as the inner city after restrictions. • Increased injury severity due to riders' alcohol intoxication. Introduction: The emergence of shared electric scooter (e-scooter) services has introduced a new mobility option in numerous urban areas worldwide. Safety concerns surrounding e-scooter riding have prompted some cities to impose bans or restrictions on shared e-scooters. This study aims to assess the impact of e-scooter restriction policies, on the spatiotemporal distribution of e-scooter injuries and factors influencing injury severity in Helsinki, Finland, in 2021 and 2022. These restrictions include banning shared e-scooter use from midnight to 5 a.m. on weekends and reducing speeds during certain hours. Method: This study employed an ordered logit model, heatmap analysis of crash locations, and temporal analysis across different time frames to achieve these objectives. Results: The findings indicate a 64% reduction in the number of e-scooter injuries after the restrictions. However, the severity of injuries experienced only a slight decrease. Notably, the trend of injury severity appeared smoother in 2022 compared to 2021, with spikes occurring from Friday to Sunday. The spatial distribution of crashes revealed that, in 2021, most crashes were concentrated in the city center, while in 2022, the crash locations were more scattered, partly due to the increased area serviced by e-scooters. The results also underscored the substantial impact of alcohol intoxication, as it significantly increased the probability of more severe injuries. Furthermore, higher age groups and people using e-scooters from 4 p.m. to 9 p.m. are more likely to experience higher injury severity after the restrictions were implemented. These research outcomes offer valuable insights for other cities, providing lessons on how to tailor policies to effectively reduce the number of e-scooter-related injuries. [ABSTRACT FROM AUTHOR]

The impacts of earthquakes on the mental health of individuals have been well-documented. Additionally, individuals frequently report experiencing dizziness akin to seasickness or carsickness. This phenomenon, termed "post-earthquake dizziness syndrome" (PEDS), has garnered increasing attention due to its unclear etiology. This study investigates the prevalence and predictors of ongoing PEDS within an adolescent population more than one year after the 2023 Kahramanmaraş earthquakes. This cross-sectional study was conducted between April 2024 and June 2024 across five cities officially designated as an "earthquake zone" by relevant authorities. The sample comprised 551 adolescents aged 11 to 18 years who were recruited from child psychiatry outpatient clinics within these cities. 402 participants (73.0 %) reported experiencing PEDS following the earthquake, while 105 (19.1 %) reported ongoing PEDS. Multivariate logistic regression analysis revealed that higher trait anxiety and post-traumatic stress disorder (PTSD) symptoms, as well as being located on a higher floor during the earthquake, were positively correlated with the persistence of PEDS symptoms. The findings underscore the potential association between PEDS and psychiatric disorders, such as anxiety and PTSD. However, the underlying mechanisms of PEDS remain elusive, requiring further research to elucidate the links between PEDS and psychiatric conditions for more effective treatment strategies. [ABSTRACT FROM AUTHOR]

• Air pollution harms firms' exports. • Air pollution reduce exports by decreasing productivity, reducing markup rates, damaging regional quality reputations, causing labour resource misallocation and strengthening environmental regulations. • The reduction effect is more pronounced among non-state-owned enterprises, heavily polluting industries, and densely populated regions. • The reduction effect also manifests a geographic spillover effect. This study examines the impact of air pollution on exports in China using a regression discontinuity design based on the Qinling Mountains-Huai River line. The findings show that air pollution harms firm exports, with a more pronounced impact on non-state-owned enterprises, heavily polluting industries, and densely populated regions. Specifically, a 1 % increase in air pollution correlates with an average reduction of 0.661 % in exports. These inhibitory effects are mainly caused by decreasing productivity, reducing markup rates, damaging regional quality reputations, causing labour resource misallocation and strengthening environmental regulations. Although air pollution spillovers from neighbouring cities may temporarily boost local firm exports and total production, they do not fully mitigate the overall negative impact of air pollution. [ABSTRACT FROM AUTHOR]

• Digital economy promotes the enhancement of industrial structure in resource-based cities significantly. • The development of digital economy can mitigate information asymmetry in inland regions significantly, making the promotion of digital economy in these areas more effective in advancing industrial sophistication compared to coastal regions. • The promotion effect of digital economy on the advancement of industrial structure shows diminishing marginal returns. • Stimulating technological innovation serves as the mechanism of enhancing the advancement of industrial structure on digital economy. With the continuous development of economy, resource-based cities in China are in urgent need of transforming and upgrading their industrial structures. This article utilizes panel data of 114 resource-based cities from 2011 to 2021 to explore the impact and mechanism of digital economy on optimizing and upgrading industrial structure. The findings, demonstrating a nonlinear relationship, reveal that digital economy promotes the advancement of the industrial structure in resource-based regions significantly. Technological innovation and financial development serve as the intermediary channel of facilitating the advancement of industrial structure in digital economy through intermediary effect analysis. Moreover, in terms of regional heterogeneity, digital economy is more effective in assisting inland resource-based cities in achieving advanced industrial structure compared to coastal areas in China. [ABSTRACT FROM AUTHOR]

• A low-carbon economy empowers urban employment via the new channels of industry agglomeration and innovation effect. • The employment-enhancing effects of a low-carbon economy are more pronounced in cities characterized by lenient environmental regulations, sufficient investment in education, and non-resource-dependent economic structures. • A low-carbon economy also contributes to an increase in the regional average wage and slows the aging trend. • This study fills the gap in the regional low-carbon economy transition and provides empirical evidence for prefectural governments. Existing studies on the employment effects of a low-carbon economy predominantly focus on sectoral dynamics instead of regions, providing limited references for prefectural policymaking. We address this gap by employing a fixed effects model and a dataset of Chinese cities from 2006 to 2020. Our findings highlight the significant contribution of a low-carbon economy to regional employment through the industry agglomeration effect and innovation effect. Heterogeneities are evident in the employment-promoting influence of a low-carbon economy, as cities with lenient environment enforcement, ample education investment, and non-resource-dependent structures benefit more significantly. Notably, a low-carbon economy exhibits a disproportionately higher employment promotion effect in cities with mid-range employment populations. In addition, we identify co-benefits of a low-carbon economy, including higher average salaries and mitigation of aging trends. These insights foster a better understanding of the low-carbon economy and offer valuable guidance for prefectural governments seeking to develop targeted low-carbon economy strategies. [Display omitted] [ABSTRACT FROM AUTHOR]