Rui Wang

Achieving urban carbon neutrality requires not only ambitious mitigation targets but also urban conditions capable of supporting implementation. However, whether cities possess such transition capacity remains insufficiently understood. Here, we develop an empirical framework to evaluate urban transition capacity across 336 Chinese cities by integrating carbon emission characteristics, policy and technology, ecological endowment, and energy potential. We identify substantial heterogeneity: 40 cities are classified as high-capacity, while most cities fall into medium- or low-capacity groups with systematically different obstacle compositions. High-capacity cities exhibit stronger conditions across all four capacity dimensions, but weighted obstacle structures shift progressively across groups. Policy and technology represent the largest relative obstacle component throughout, whereas the contribution of carbon emission characteristics increases markedly as transition capacity declines. Together, these results link multidimensional capacity assessment with group-specific obstacle diagnostics across a large urban system. The findings question the suitability of uniform mitigation strategies across heterogeneous urban contexts and support capacity-oriented governance that aligns transition priorities with city-specific conditions.

Accessibility to community pharmacy service (CPS) is a key concern in public health and spatial planning. Although on-demand delivery may expand service opportunities through digital platforms and third-party riders, its contribution to CPS potential accessibility and equity remains underexplored. Using 647 community units in central Tianjin, China, and survey-derived parameters from 600 questionnaires (83.5% response rate), this study extends the Two-Step Floating Catchment Area (2SFCA) method by incorporating multidimensional supply capacity and a time-decay function weighted by modeled supplier-selection probability. Communities were classified into four groups according to geographic and digital barriers, and Geodetector was applied to examine factors associated with spatial heterogeneity in potential accessibility. Results reveal substantial group differences. In-store dispensing provides higher potential accessibility for groups with low geographic barriers, whereas on-demand delivery shows a relative accessibility advantage for groups facing high geographic or dual barriers. For these groups, delivery is also associated with a more equitable distribution of potential service opportunities, with Gini coefficients 0.08-0.12 lower than those for in-store dispensing. Factor interactions generally show greater explanatory power than individual factors, with prominent associations shifting from population size to interactions involving age structure and socioeconomic characteristics. These findings support differentiated pharmacy planning and closer coordination between offline mobility and online delivery networks.

Fiscal shocks in post-land-finance China are weakening the funding basis of capital-intensive metro public-private partnership (PPP) projects, but the system-level mechanism through which public fiscal stress becomes subcontractor-level financial viability pressure remains underexplained. This study examines a section-level metro PPP project ecosystem in a sub-provincial Chinese city to trace this transmission mechanism and its financial implications. The analysis combines de-identified audit evidence and interviews with a scenario-based structural NPV model and 800,000 model-generated Monte Carlo realizations under calibrated institutional scenarios. The evidence indicates that quasi-bureaucratic SPV internal capital-market arrangements convert fiscal shortfalls into vertical and horizontal cross-subsidization practices, preserving short-term project continuity while shifting cash-flow pressure downstream. This condition is defined as a strategic resilience trap: practices that preserve short-term project continuity while potentially eroding the project ecosystem’s long-term adaptive capacity. Under calibrated assumptions, improving the contract-payment channel reduces model-generated losses by approximately 4%, suggesting that payment punctuality addresses only one part of the wider internal capital-market mechanism.

Demand-side management is increasingly important for low-carbon transport governance. However, many studies assume relatively stable travel preferences and pay limited attention to behavioural changes under sudden external shocks. This study proposes an Event–Behaviour–Resilience framework and applies Natural Language Processing to Sina Weibo data to examine travel responses to extreme heat and refined oil price adjustments. The results show asymmetric response patterns. Oil price increases were associated with cost-based low-carbon substitution, with new-energy vehicle intentions accounting for 64.4% of the share. In contrast, extreme heat was associated with both trip reduction and motorised travel. Travel reduction reached 52.4%, while ride-hailing or taxi responses accounted for 24.6%. A quadratic fitting analysis identified 38.0–39.0 °C as an observed transition interval, within which high-carbon motorised willingness began to exceed low-carbon slow mobility willingness. Group-level analysis showed unequal behavioural flexibility. While 80.0% of the general population reduced travel under extreme heat, the forced mobility group showed limited travel reduction and maintained a high level of low-carbon willingness at 86.87%. XGBoost-SHAP results indicated that temperature, emotional valence, and behavioural constraints contributed to low-carbon mobility intention. These findings suggest that behavioural responses can help identify spatial interventions for low-carbon transport, especially in relation to heat exposure, mobility flexibility, and access to adaptive travel options.

Due to the limited availability of medical facilities and the urgency and irreplaceability of medical-seeking behaviors, the transportation processes used to access these resources inherently result in high carbon emissions. Unfortunately, pediatric medical facilities are among the least substitutable destinations, making it challenging to reduce travel-related CO₂ emissions by traditional means such as decreasing travel frequency or optimizing transportation means. This study proposes enhancing the spatial allocation of pediatric medical facilities to effectively reduce travel-related CO₂ emissions. This study selects 27 hospitals with pediatric departments in Tianjin as the research subject. It introduces a model for measuring travel-related CO₂ emissions for pediatric medical-seeking, STIRPAT, and ridge regression models as well as conducts simulations under various scenarios to test the hypotheses. Therefore, methods for enhancing the spatial allocation of pediatric medical facilities are proposed. The results show that (1) travel-related CO₂ emissions for pediatric medical-seeking are the highest in the city center, outpatient-related CO₂ emissions surpass inpatient ones, and children’s hospital-related CO₂ emissions are higher than those related to comprehensive hospitals, from which potential carbon reduction points can be explored; (2) children’s hospitals with multibranch and composite functional allocations can significantly reduce CO₂ emissions; (3) comprehensive hospitals can further alleviate CO₂ emissions from children’s hospitals by enhancing the medical level, transportation infrastructure, population distribution, and other spatial environmental factors; (4) from the perspective of low-carbon travel and equity, a spatial allocation strategy should be adopted for children’s hospitals that includes multiple branches and composite functions, while comprehensive hospitals should focus on service capacity, parity, supply–demand ratio, and the population density of children.

The development of differentiated emission reduction strategies plays an important role in achieving carbon compliance targets. Each city should adopt carbon reduction strategies according to its carbon emission characteristics. China is a vast country, and there are significant differences between cities. Therefore, this study classifies 340 Chinese cities according to their carbon emission characteristics since 2020 and proposes differentiated emission reduction strategies accordingly. The results of the research show that Chinese cities can be divided into four categories, and they can strive to achieve their carbon peak targets by adopting differentiated emission reduction strategies. In the baseline scenario, Chinese cities will not be able to meet the peak carbon target by 2030. In the differentiated scenario, eco-agricultural cities, industry-led cities, and high-resource-availability cities will be able to achieve peak carbon by 2030. Unfortunately, resource-poor cities will not reach their peak. However, the extent to which their total carbon emissions contribute to the achievement of national goals is low, and their carbon emissions can be traded off for economic development by appropriately relaxing the constraints on carbon emissions. Therefore, in order to achieve China’s peak carbon goal, this study proposes emission reduction recommendations that should be adopted by different types of cities to form differentiated emission reduction strategies.

Low-carbon management plays an important role in mitigating climate change and adapting to it. Localities should adopt differentiated low-carbon management policies according to the state of their environment. To help formulate specific and realistic low-carbon management policies, this paper took into account specific low-carbon management sectors. Likewise, it carefully considered the differences in various resource endowments and proposed a method for evaluating low-carbon management efficiency and potential. The method was applied to an empirical study from 2015 conducted on 1771 Chinese counties. Significant spatial heterogeneity was found during the research. The counties bordering central and Western China and the ones in the southeast coastal areas showed higher efficiency in the industrial sector. Southern and Northern China had higher efficiency in the housing and transportation sector, respectively. Moreover, counties in remote areas showed more potential in the industrial sector. Central China had higher potential in the housing sector, while counties bordering provinces had more potential in the transportation sector. Therefore, Chinese counties were divided into eight management zones where differentiated management strategies were identified to shape low-carbon management policies.

CO₂ is the main greenhouse gas. Urban spatial development, land use, and so on may be affected by CO₂ and climate change. The main questions studied in this paper are as follows: What are the drivers of CO₂ emissions of expanding megacities? How can they be analyzed from different perspectives? Do the results differ for megacities at different stages of development? Based on the XGBoost model, this paper explored the complex factors affecting CO₂ emissions by using data of four Chinese megacities, Beijing, Tianjin, Shanghai, and Chongqing, from 2003 to 2017. The main findings are as follows: The XGBoost model has better applicability and accuracy in predicting carbon emissions of expanding megacities, with root mean square error (RMSE) as low as 0.036. Under the synergistic effect of multiple factors, population, land size, and gross domestic product are still the primary driving forces of CO₂ emissions. Population density and population become more important in the single-factor analysis. The key drivers of CO₂ emissions in megacities at respective developmental stages are different. This paper provides methods and tools for accurately predicting CO₂ emissions and measuring the critical drivers. Furthermore, it could provide decision support for megacities to make targeted carbon-emission-reduction strategies based on their own developmental stages.