交通与城市环境

Amid global concerns regarding environmental pollution and carbon emissions, the influence of the built environment on travel behavior (e.g., car ownership, vehicle usage, and subsequent pollutant emissions) has taken center stage. This study delves into this intricate relationship, aiming to elucidate the causal links that have historically been obscured by residential self-selection bias. Leveraging China’s unique socialist housing relocation policies, we employed a randomized experimental approach complemented by structural equation modeling. Our findings underscore the strong causal relationship between the built environment and pollutant emissions resulting from travel behavior. Specifically, this study revealed that certain urban planning choices can significantly impact vehicle ownership patterns, vehicle kilometers traveled, and pollutant emissions. The dual contributions of this study lie in its innovative methodological approach, which provides a blueprint for future global research, and its practical implications, offering actionable insights for urban policymakers.

Vehicle electrification has been recognized for its potential to reduce emissions of air pollutants and greenhouse gases in China. Several studies have estimated how national-level policies of electric vehicle (EV) adoption might bring very large environmental and public health benefits from improved air quality to China. However, large-scale adoption is very costly, some regions derive more benefits from large-scale EV adoption than others, and the benefits of replacing internal combustion engines in specific cities is less known. Therefore, it is important for policymakers to design incentives based on regional characteristics – especially for megacities like Shanghai – which typically suffer from worse air quality and where a larger population is exposed to emissions from vehicles. Over the past five years, Shanghai has offered substantial personal subsidies for passenger EVs to accelerate its electrification efforts. Still, it remains uncertain whether EV benefits justify the strength of incentives. The purpose of our study is to evaluate the health and climate benefits of replacing light-duty gasoline vehicles (ICEVs) with battery EVs in the city of Shanghai. We assess health impacts due to ICEV emissions of primary fine particulate matter, NOx, and volatile organic compounds, and to powerplant emissions of NOx and SO2 due to EV charging. We incorporate climate benefits from reduced greenhouse gas emissions based on existing research. We find that the benefit of replacing the average ICEV with an EV in Shanghai is US$6400 (2400-14,700), with health impacts of EVs about 20 times lower than the average ICEV. Larger benefits ensue if older ICEVs are replaced, but replacing newer China ICEVs also achieves positive health benefits. As Shanghai plans to stop providing personal subsidies for EV purchases in 2024, our results show that EVs achieve public health and climate benefits and can help inform policymaking strategies in Shanghai and other megacities.

The scale-up of urban electric vehicle (EV) fleets, driven by environmental benefits, is resulting in surging aggregate energy demands that may reshape a city's power supply. This paper establishes an integrated data-driven assessment model for investigating the energy use (kWh) patterns and charging load (kW) profiles of urban-scale EV fleets. To this end, urban EV operating and operational datasets are linked with climate data and vehicle specifications. Four vehicle fleet types are distinguished: private, taxi, rental, and business fleets. Statistical models regarding distribution analysis, spectrum analysis, and identical distribution tests are employed to analyze the patterns of driving distances, energy consumption, and shares of active charging EVs. The minute-level changes in charging EV numbers and aggregate charging power are examined to reflect the grid load impact. The results show that private light-duty EVs in Beijing consume an average of 9.1 kWh/day, with more charging activities on Fridays. The primary load peaks of light-duty EVs in Beijing usually occur between 11 p.m. and 1 a.m., attributable chiefly to the private fleet's midnight peak load estimated at 28 % of the total daily charging private EV count multiplied by 5.5 kW/EV. Secondary peaks occur between 8 a.m. and 10 a.m. on weekdays for private fleets, and at 4 p.m. for public fleets. Our work can be extensively used for analyses on transport emissions, urban power supply, infrastructure build-ups, and policymaking.

China’s civil aviation market has rapidly expanded, becoming the world’s second-largest. However, the air quality and health impacts caused by its aircraft emissions have been inadequately assessed. Here, we leverage an updated emission inventory of air pollutants with improved temporal and spatial resolution based on hundreds of thousands of flight trajectories and simulate aviation-attributable contributions to ground-level air pollution in China. We find that in 2017, the annual-average aviation-attributed PM2.5 and O3 concentrations were 0.4–1.5 and 10.6–14.5 μg·m–3, respectively, suggesting that aviation emissions have become an increasingly important source of ambient air pollution. The contributions attributable to high-altitude emissions (climb/cruise/descent) were comparable to those at low altitudes (landing and takeoff). Aviation-attributed ambient PM2.5 and O3 exposures are estimated to have caused about 67,000 deaths in China in 2017, with populous coastal regions in Eastern China suffering the most due to the dense aviation activity. We recommend that industrial and policy stakeholders expedite an agenda of regulating air pollutants harmonized with decarbonization efforts for a more sustainable aviation future.

Road traffic injuries are a leading cause of socio-economic loss in East Asia Summit (EAS) countries. A regular performance rating to monitor progress and calibrate interventions is crucial for road safety improvement, helping to save human lives and reducing economic losses. To this end, we propose a new and easy-to-adapt multi-criteria decision-making method for systematically rating the road safety performance of the EAS countries, the preference selection index with principal component analysis of RIDIT scores (PSI-PRIDIT) (scores of a distribution relative to an identified distribution integral transformation). Using the results from other classical methods as a reference, we rank the EAS countries robustly and place them into three groups over the last decade (2009–2019), based on the composite road safety development index. Our findings should be useful for EAS countries to detect underlying problems and identify best practices, as well as provide government officials, policymakers, and practitioners with meaningful guidelines on the adoption of successful road safety measures. Overall, the proposed rating framework should help to strengthen the institutional capacity for road safety management and addresses road safety issues.

Road traffic crashes have been a leading cause of death in Southeast Asian countries, which greatly harms the development of countries and affects the livelihood of countless families in this region. In this context, a regular review of road safety attainment is needed to understand why road crashes happen and to better guide the ongoing policymaking and implementation of effective countermeasures as well as next-level strategies. This study introduces an easy-to-use, effective, and systematic methodology for multi-criteria decision-making, CRiteria Importance Through Inter-criteria Correlation (CRITIC) - ELimination and Et Choice Translating REality (ELECTRE) - Fuzzy C-Means (FCM) (CRITIC-ELECTRE-FCM). Its purpose is to appraise the road safety attainment of 11 countries in Southeast Asia. Accompanied by the robustness of analyses with other widely used methods, these countries are ranked and grouped into several levels regarding their road safety attainment over the past decade (2009–2018). The findings provide government officials, policymakers, and any stakeholders of these countries with meaningful information (e.g., what has been done well and what has not) and instructive guidance for future action. Overall, the proposed appraisal system serves as an efficacious policymaking support for countries in the region to review road safety attainment, develop future strategies and policies, and implement safety management.

Housing reform in socialist China has incurred considerable restructuring and transformation of urban space and society. Yet its specific socio-spatial outcomes have not been fully investigated from the perspective of housing type at the meso- and micro-levels. This study attempts to fill the gap by examining the nature and magnitude of the consequences of housing reform and the corresponding effects on mobility. Specifically, based on census data and a mobility survey, this paper combines statistical breakdowns and structural equation modeling to capture the socio-spatial differentiation of urban structure resulting from housing reform and its influences on individual vehicle kilometers traveled (VKT) and transportation walking. The results reveal that: (1) different types of housing tend to feature internally homogeneous populations in terms of socio-economic composition and socio-psychological condition, with pronounced social stratification; (2) residents in different types of housing display dramatically different travel styles, with substantial mobility inequities; (3) social differentiation appears to have spatial determinants; in particular spatial segregation contributes to increasing social exclusion; (4) the effects of spatial and social characteristics on mobility are led by housing type; and (5) individual mobility patterns are shaped by the joint influences of spatial and social dimensions of housing differentiation. The findings contribute to further understanding of socio-spatial differentiation in countries with a transitional housing market, suggesting that the design of land-use policies should recognize their social effects and that urban mobility planning practices should deliver sustainability that serves a diverse population, including in particular disadvantaged groups in public and replacement housing. This study serves as a mirror to observe the urban transition compared to other political economies and adds additional richness and diversity to the theoretical debates on the issue of socio-spatial differentiation and empirical evidence on residential and mobility inequities across global contexts.

Experimental designs have been recognized as the gold standard for establishing causal mechanisms. However, the application of such designs is complicated by factors such as excessive costs, time consumption, ethical concerns, and political impossibility. Nevertheless, the Chinese government’s replacement housing efforts provide a unique randomized experiment for exploring the causal effects of the built environment on travel behavior. Accordingly, based on a large-scale survey on travel patterns under an experimental design in Shanghai, this study employs a two-step modeling approach, involving logit and Tobit models, to identify the built environment’s effects on auto ownership and vehicle kilometers traveled (VKT). We found that transit service improvements play a stronger role in reducing auto-drive than compact and diverse land-use characteristics. Increasing residential and employment density, as well as land-use mix, discourages car ownership, which in turn reduces VKT, but with lower elasticities than transportation system variables. The findings provide additional evidence and referential estimate for how land-use and transport strategies and policies designed to create a compact, mixed-use, and highly accessible built environment can be used in reducing auto driving. This study expands the VKT reduction elasticities’ database regarding the built environment across global spatial contexts, serving as a model for similar studies elsewhere in the world.

Intra-city Public Charging Stations (PCSs) play a crucial role in promoting the mass deployment of Electric Vehicles (EVs). To motivate the investment on PCSs, this work proposes a novel framework to find the optimal location and size of PCSs, which can maximize the benefit of the investment. The impacts of charging behaviors and urban land uses on the income of PCSs are taken into account. An agent-based trip chain model is used to represent the travel and charging patterns of EV owners. A cell-based geographic partition method based on Geographic Information System is employed to reflect the influence of land use on the dynamic and stochastic nature of EV charging behaviors. Based on the distributed charging demand, the optimal location and size of PCSs are determined by mixed-integer linear programming. Västerås, a Swedish city, is used as a case study to demonstrate the model's effectiveness. It is found that the charging demand served by a PCS is critical to its profitability, which is greatly affected by the charging behavior of drivers, the location and the service range of PCS. Moreover, charging price is another significant factor impacting profitability, and consequently the competitiveness of slow and fast PCSs.

Overseeing road safety progress at regular intervals has and will continue to be advocated as the most promising means to achieve continuous safety improvement. Thus, a scientific approach that can be capable of doing so is disparately required. This study aims to propose a brand-new and efficient methodology for overseeing overall road safety progress at the regional level. To this end, CV-PROMETHEE Ⅱ-JSS, which seamlessly incorporates Coefficient of Variation (CV), Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), and Joint Singular value decomposition and Semi-discrete decomposition (JSS) in an integrative manner, is developed. Specifically, this is designed to combine the retrospective examination and benchmarking analysis in a comprehensive and systematic framework. Based on the proposed methodology, the road safety development of the European Union (EU) Member States is examined over the past decade (2010–2020), whilst simultaneously benchmarking safety performance looking forward to the next decade (2020–2030). As a result, a detailed picture of changes in road safety for each country is quantitatively depicted, providing policymakers with deeper insights into how progress was achieved. The appropriate benchmarks are also scientifically identified for each laggard member to use as a meaningful reference, which largely avoids the need for reinventing the wheel and trial and error approaches. This study provides the EU27 + 3 countries with a practical paradigm to perform both diagnostics and treatment to improve overall road safety levels in an effective way; supporting the government officials and policymakers in the charting of future strategic directions and intervention priorities, and helping them define ways to accelerate action on proven strategies and policies for better lives. Moreover, this study enriches the existing Multi-Criteria Decision-Making (MCDM) mechanism by introducing the CV-PROMETHEE Ⅱ-JSS, and implies its feasibility and effectiveness in future MCDM cases involving safety-related issues.

Measuring road safety achievement through persistent monitoring of subjects, such that they can learn from one another, has been widely encouraged by various countries to support policymaking. In recent decades, the Asia-Pacific Economic Cooperation (APEC) countries have been working together to improve road safety, considering it an important constituent and reflection of their economic development. However, no uniform road safety measurement framework is currently available across the APEC. To this end, the current study develops a practical and efficient methodology, namely, the entropy weight method (EWM) – grey relational analysis (GRA) – singular value decomposition (SVD) (EWM-GRA-SVD), providing government officials and policymakers with a replicable framework for reporting the road safety achievement of countries. The EWM is employed to obtain the weights of the set of indicators, as the weighting inputs of GRA, to form a composite score for ranking, where the SVD is embedded in the GRA for grouping by means of extracting singular values. Using the proposed model, best-performing and underperforming countries are distinguished, whereby each country could learn from others within their assigned group based on an overview of achievements and progress in road safety over the past decade. The results enable decision-makers and policymakers to develop action plans and consider necessary interventions promptly and effectively.

Large numbers of people in many countries report being lonely with rates highest among the very old. Does the built environment affect loneliness among older people and if so, how? Using a scoping review, we examined associations between loneliness and built environments at the block, neighborhood, and city scales. The (1) neighborhood environment has received most attention. Research has also examined (2) urban contexts, (3) housing, and (4) transportation access. Findings are mixed with the stronger evidence that local resources, walkability, overall environment quality, housing options, and nearby transportation alternatives can help combat loneliness.

Urban green and open space are important components of achieving the goal of planning sustainable cities, by offering health benefits to urban dwellers and providing socio-economic and environmental benefits to society. Recent literature studied the usage of urban parks, however, few has addressed seasonal fluctuations of park visitor volume, let alone seasonal variations of home-park travel distances and park service areas. This paper not only empirically shows the seasonal variations of park visits but also examines links between the park visit patterns and spatial characteristics of the case parks. Applying spatial analysis methods to location data of over 1 million anonymous mobile phone samples collected from January to December 2011, we analyzed the seasonal variations in six medium-sized urban parks, of which size falls under the category of ‘district parks,’ in central Tokyo. We also conducted content analysis of a Japanese place review website to understand visitor perceptions of the case parks. On the other hand, park spatial characteristics data were collected and summarized through various ways including field observation and satellite image analysis. The results show that (1) while notable seasonal variations of park visitor volume and park service area existed in all case parks, the degree of variation also differed from park to park; (2) spatial characteristics of parks were closely interlinked to seasonal cultural events, to visitor perceptions, and consequently to seasonal fluctuations of the park visit patterns. Lessons learned from the policy perspective include highly diverse user groups visit these medium-sized urban parks than what the typical guidelines assume, and seasonal patterns of their visits considerably vary from park to park, interacting with spatial characteristics of the parks. Hence, the urban park planning process should consider specific and detailed characteristics of parks and allocate resources to respond to dynamic park visit patterns beyond generic guidelines.

 

Introduction

An increasing number of walking studies discussed the relationship of walking with attitudes and perceptions. However, the findings were not consistent, and few studies examined the relationship between walking and attitudes to overall mobility and multiple modes. In this paper, we contribute to the debates by exploring the relationship between walking for transport and broad attitudes to urban mobility and transport modes.

Methods

Using a clustered random sample survey conducted in a second-tier city in China (N=1,048), we hypothesized that people with different attitudes have different amounts of walking for transport. Data analysis methods involved descriptive statistics, t-tests, Analysis of Variance (ANOVA), hierarchical logistic models, and hierarchical linear models.

Results

Positive attitudes and perceptions regarding multiple transport modes and related environments were associated with some walking for transport. T-tests indicated that those with different attitudes walked different amounts. Regression models showed that associations between attitudes and odds of people walking varied between genders. Males who perceived bus frequency was not a problem were more likely to walk. Females tended to walk when viewing transportation in the city as convenient. Both findings contribute to the understanding that positive perceptions of overall mobility in the city were associated with higher odds of walking. Meanwhile, among those who did walk, those with positive attitudes towards pedestrian safety crossing streets and those perceiving traffic jams as a problem in their daily trips spent more time walking.

Conclusion

This paper concludes that positive broad attitudes and perceptions of overall mobility and all transport modes are related to more walking activities. A better understanding of such relationships can provide a reference point for urban policies aiming at promoting walking for transport.

 

Objectives: This paper explores how the building-scale built environment is associated with self-rated health, examining differences in this association among younger, middle-aged, and older age groups. Features examined included building type, building condition, and sidewalk presence in front of dwellings.
Background: Understanding how the relationships between built environments and health vary across age groups helps to build a healthy environment for all. However, most studies have concentrated on the neighborhood or indoor environment, rather than whole buildings, and few have compared age groups.
Methods: This study analyzed survey data from 1,019 adults living in 40 neighborhoods in Chengdu, China, recruited through a clustered random sampling approach. It used a Bayesian logistic mixed effects model with interaction terms between age group indicators and other variables.
Results: Significant differences exist in the relationships of self-rated health with some environmental and other indicators among age groups. For older people, living in multi-floor buildings, having a household smoker, and undertaking fewer hours of weekly exercise were associated with lower odds of reporting good, very good, or excellent health. These relationships were not identified among middle-aged and younger people. More education was associated with higher odds of reporting better health among older and middle-aged groups.
Conclusions: Older people experience more health-related challenges compared to middle-aged and younger people. However, among the examined built environmental factors, building type was the only significant factor related to self-rated health among older people. To promote health among older people, this study recommends adding elevators in the multi-floor buildings.

Due to spatial heterogeneity worldwide, results from studies examining the effect of residential self-selection on travel behavior vary substantially. As a result of housing reform, the unique housing allocation system in China is a prime example of a context where the self-selection effect may conflict with international knowledge. Using a sample of 3836 residents, whom are living in Transit-Oriented Development (TOD) and non-TOD neighborhoods in Shanghai, this study untangles the effects that the built environment and residential self-selection have on travel behavior, in the context of diversified housing types in urban China. Specifically, this paper employs propensity score matching (PSM) to quantitate the relative importance of the built environment itself, verses residential self-selection, in influencing travel behavior for each of the housing types. The results show that the residential self-selection effect in the four types of housing (work-unit, commodity, public, and replacement) accounts for 15.2%, 30.7%, 18.5%, and 5.9% of the total impact on vehicle kilometers traveled (VKT), respectively. These findings expand the international database of point estimates in the relative contribution of self-selection toward the impact on travel behavior across global contexts, providing a comprehensive framework for similar studies on self-selection in other parts of the world.

Intra-city Public Charging Stations (PCSs) play a crucial role in promoting the mass deployment of Electric Vehicles (EVs). To motivate the investment on PCSs, this work proposes a novel framework to find the optimal location and size of PCSs, which can maximize the benefit of the investment. The impacts of charging behaviors and urban land uses on the income of PCSs are taken into account. An agent-based trip chain model is used to represent the travel and charging patterns of EV owners. A cell-based geographic partition method based on Geographic Information System is employed to reflect the influence of land use on the dynamic and stochastic nature of EV charging behaviors. Based on the distributed charging demand, the optimal location and size of PCSs are determined by mixed-integer linear programming. Västerås, a Swedish city, is used as a case study to demonstrate the model's effectiveness. It is found that the charging demand served by a PCS is critical to its profitability, which is greatly affected by the charging behavior of drivers, the location and the service range of PCS. Moreover, charging price is another significant factor impacting profitability, and consequently the competitiveness of slow and fast PCSs.

Urban parks can offer both physical and psychological health benefits to urban dwellers and provide social, economic, and environmental benefits to society. Earlier research on the usage of urban parks relied on fixed distance or walking time to delineate urban park catchment areas. However, actual catchment areas can be affected by many factors other than park surface areas, such as social capital cultivation, cultural adaptation, climate and seasonal variation, and park function and facilities provided. This study advanced this method by using mobile phone data to delineate urban park catchment area. The study area is the 23 special wards of Tokyo or tokubetsu-ku, the core of the capital of Japan. The location data of over 1 million anonymous mobile phone users was collected in 2011. The results show that: (1) the park catchment areas vary significantly by park surface areas: people use smaller parks nearby but also travel further to larger parks; (2) even for the parks in the same size category, there are notable differences in the spatial pattern of visitors, which cannot be simply summarized with average distance or catchment radius; and (3) almost all the parks, regardless of its size and function, had the highest user density right around the vicinity, exemplified by the density-distance function closely follow a decay trend line within 1-2 km radius of the park. As such, this study used the density threshold and density-distance function to measure park catchment. We concluded that the application of mobile phone location data can improve our understanding of an urban park catchment area, provide useful information and methods to analyze the usage of urban parks, and can aid in the planning and policy-making of urban parks.