Minan Yang

Coordinating public service supply and demand is essential to urban social sustainability. This study examines ten suburban districts of Beijing at six observation points from 2015 to 2024 and develops an integrated framework encompassing resource endowment, demand pressure, supply–demand matching, and spatial equity. Resource endowment and demand pressure are measured using spatial accessibility and objective weighting methods, while relative matching coefficients, Lorenz curves, and Gini coefficients are employed to evaluate spatial mismatch and equity. The results reveal a shift toward a dynamic polycentric supply pattern, persistent relative undersupply in Tongzhou and Daxing, and dimension-specific deficits in several otherwise balanced districts. Overall spatial equity improved during the study period, although localized mismatches remained. Public service planning should therefore move from uniform expansion toward demand-responsive, place-specific, and service-specific optimization.

Whether young people can equitably access everyday living and shopping facilities has become a key indicator of fairness in youth-friendly cities. However, existing research has paid limited attention to young people’s daily activity spheres, particularly to how linear urban forms may intensify core–periphery disparities in accessibility. Using Lanzhou, a typical Chinese strip city, as a case study, this paper develops a multidimensional evaluation framework integrating coverage, richness, and sharing. Drawing on 1650 youth questionnaires and detailed geospatial data, it applies a preference-based behavioural accessibility model in conjunction with the Gini coefficient to examine the spatial equity of daily shopping facilities. Results indicate that Lanzhou’s facilities exhibit a pattern of central concentration and peripheral scarcity. Chengguan and Anning districts form highly accessible cores, supported by dense commercial areas and university resources. In contrast, Qilihe and Xigu suffer from pronounced facility deficits, with walking coverage rates of five to fifteen minutes below 70%. Accessibility patterns reveal coexisting contradictions of “high supply but low access” and “low supply with difficult access”. Equity metrics indicate a moderate overall level (Gini = 0.272), yet notable inter-district disparities persist, with peripheral areas imposing higher access costs on young residents. The study confirms a persistent spatial dilemma whereby the quantity of facilities does not guarantee equitable access. It argues that urban governance should shift from equal allocation towards demand-responsive and perceived-equity approaches, thereby extending daily shopping opportunities to peripheral zones. Enhancing neighbourhood-scale connectivity through pedestrian and cycling networks would improve both practical usability and spatial fairness for young urban populations.

This study focuses on the challenges of resident mobility in low-density areas. Amid China’s rapid urbanization, rural landscapes and travel patterns are undergoing significant transformation. Using Lanzhou’s rural areas as a representative case study, this research employs questionnaire surveys to collect data. It applies a multi-nominal logit (MNL) model to examine factors influencing travel mode choices and utilizes structural equation modeling (SEM) to assess travel satisfaction—a composite metric derived from residents’ subjective evaluations of convenience, cost, time, and comfort. Findings indicate that private cars and public transportation are the primary travel modes. The MNL model reveals that age and destination accessibility significantly influence travel choices. SEM path analysis further shows that annual household income has a direct positive effect on satisfaction, while age exerts an indirect negative influence through mediating variables. Female satisfaction levels were significantly lower than those of males. Both road density and perceived infrastructure quality significantly enhanced satisfaction, while destination accessibility may exert a slight negative indirect effect by increasing travel expectations. The study theoretically enriches research on rural travel patterns and provides practical insights into rural transportation planning and infrastructure development.

Mitigating traffic-related carbon emissions is pivotal for achieving carbon peaking targets and advancing sustainable urban development. This study employs spatial autocorrelation and high-low clustering analyses to analyze the spatial correlation and clustering patterns of urban road traffic carbon emissions in Shaanxi Province. The spatiotemporal evolution and structural impacts of emissions are quantified through a systematic framework, while the GTWR (Geographically Weighted Temporal Regression) model uncovers the multidimensional and heterogeneous driving mechanisms underlying carbon emissions. Findings reveal that road traffic CO₂ emissions in Shaanxi exhibit an upward trajectory, with a temporal evolution marked by distinct phases: “stable growth—rapid increase—gradual decline”. Emission dynamics vary significantly across transport modes: private vehicles emerge as the primary emission source, taxi/motorcycle emissions remain relatively stable, and bus/electric vehicle emissions persist at low levels. Spatially, the province demonstrates a pronounced high-carbon spillover effect, with persistent high-value clusters concentrated in central Shaanxi and the northern region of Yan’an City, exhibiting spillover effects on adjacent urban areas. Notably, the spatial distribution of CO₂ emissions has evolved significantly: a relatively balanced pattern across cities in 2010 transitioned to a pronounced “M”-shaped gradient along the north–south axis by 2015, stabilizing by 2020. The central urban cluster (Yan’an, Tongchuan, Xianyang, Baoji) initially formed a secondary low-carbon core, which later integrated into the regional emission gradient. By focusing on the micro-level dynamics of urban road traffic and its internal structural complexities—while incorporating built environment factors such as network layout, travel behavior, and infrastructure endowments—this study contributes novel insights to the transportation carbon emission literature, offering a robust framework for regional emission mitigation strategies.

With the increase in urban–rural disparities in China, rural public transportation systems in low-density areas face unique challenges, especially in the contexts of sparse population, complex topography, and uneven resource allocation; research on public transportation in low-density areas has had less attention compared to high-density urban areas. Therefore, how to solve the dilemma of public transportation service provision in low-density rural areas due to sparse population and long travel distances has become an urgent problem. In this paper, a dynamic optimization model based on a two-layer planning framework was constructed. The upper layer optimized the topology of multimodal transportation nodes through the Floyd shortest path algorithm to generate a composite network of trunk roads and feeder routes; the lower layer adopted an improved Logit discrete choice model, integrating the heterogeneous utility parameters, such as time cost, economic cost, and comfort, to simulate and realize the equilibrium allocation of stochastic users. It was found that the dynamic game mechanism based on the “path optimization–fairness measurement” can optimize the travel time, mode, route, and bus stop selection of rural residents. At the same time, the mechanism can realize the fair distribution of rural transportation network subjects (people–vehicles–roads). This provides a dynamic, multi-scenario macro policy reference basis for the optimization of a rural transportation network layout.

Against the backdrop of the newly constructed urban rail transit network and the ongoing urbanization of strip-shaped cities, this study investigates the distribution and evolution of commercial points of interest (POIs) in the central urban area of Lanzhou. The research analyzes data from three distinct years (2016, 2018, and 2020) to observe the temporal changes in commercial entities before and after the establishment of metro stations. Stable explanatory variables influencing the distribution and evolution of commercial POIs are identified, including rail transit passenger flow, demographic characteristics of the working and residential populations surrounding stations, as well as building and road densities in their vicinity. Through statistical analysis and model construction, these influencing factors are systematically evaluated to establish a relatively stable linear regression equation that quantifies the weights assigned to each factor. This study enhances our understanding of how urban rail transit impacts urban vitality within belt-shaped cities while elucidating its positive role in shaping development patterns unique to such areas. It clarifies the relationship between changes in urban vitality and spatial configuration, thereby providing valuable insights for urban planners and decision-makers. Furthermore, this research can serve as a reference model for other strip-shaped cities seeking to optimize their distribution of urban vitality through the effective utilization of urban rail transit systems.

Under the context of low-carbon travel, promoting the green and environmentally friendly upgrade of urban transportation and optimizing urban transportation structures are of great significance in reducing carbon emissions. Exploring the pathways and methods to achieve green and low-carbon goals in urban transportation is a key research objective. Accordingly, this study constructs a multi-objective optimization model to optimize the transportation structure of Lanzhou City and quantitatively verifies the optimization effects through carbon emission calculations and coordination evaluations. The results indicate that (1) optimizing urban transportation structures can reduce energy consumption and emission levels but cannot achieve the “carbon peaking” goal; (2) developing urban rail transit has a significant positive impact on energy saving and emission reduction; (3) the development of green transportation is closely integrated with and mutually influenced by slow-moving transportation, showing both synergy and constraints; and (4) under the comprehensive restriction scenario, despite higher energy consumption and emission values, better coordination is achieved, making it the most suitable optimization plan aligned with the green transportation development concept.

Improvement of the walkability of the 15-min community life circle can enhance convenience for residents to obtain daily service facilities. In this paper, by obtaining the Point of Interest (POI) data of daily facilities used by Shanghai residents, we calculate the walk scores of community residents within 15-min walking distance using the walkability assessment tool and analyze the results with population density for spatial correlation. The results show that communities with high walk scores are concentrated in central areas, with low walk scores are scattered in the suburbs of the city. Walking scores are high for access from communities to bus stops and commercial services but low for access to parks and primary schools. The formation of a compact and accessible spatial layout can significantly improve the walkability of the community. Walkability is not only related to the construction of facilities in terms of quantity and space but is also influenced by the degree of spatial clustering in the community. It needs to be reasonably configured in conjunction with the spatial distribution of the community in order to effectively improve the utilization of facilities. Finally, community walkability is significantly and positively correlated with population density.