In China, new-energy vehicles are viewed as the ultimate goal for the automobile industry, given the current focus on the “dual-carbon” target. Therefore, it is important to promote the sustainable development of this new-energy market and ensure a smooth transition from fuel-driven vehicles to new-energy vehicles. This study constructs a tripartite evolutionary game model involving vehicle enterprises, consumers, and the government. It improves the tripartite evolutionary game through the mechanisms of dynamic and static rewards and punishments, respectively, using real-world data. The results show the following. (1) A fluctuation is present in the sales of new-energy vehicles by enterprises and the active promotional behavior of the government. This fluctuation leads to instability, and the behavior is difficult to accurately predict, which is not conducive new-energy vehicles’ promotion and sales. (2) A static reward and punishment mechanism can change the fluctuation threshold or peak value. Nevertheless, the stability of the system’s strategy is not the main reason that the government has been actively promoting it for a long time. However, enterprises are still wavering between new-energy and fuel vehicles. (3) The linear dynamic reward and punishment mechanism also has its defects. Although they are considered the stability control strategy of the system, they are still not conducive to stability. (4) The nonlinear dynamic reward and punishment mechanism can help the system to achieve the ideal stabilization strategy.

Against the backdrop of China’s “dual carbon” goals of achieving carbon peaking by 2030 and carbon neutrality by 2060. Traditional qualitative evaluations struggle with subjectivity; therefore we apply the quantitative PMC Index to systematically assess smart energy policies. This research systematically analyzes 16 representative Chinese smart energy policies using the PMC model, combined with content analysis. An integrated analytical framework was constructed to examine PMC applications across different energy policy fields. Results demonstrate that China’s smart energy policies achieved excellent performance, with an average PMC score of 7.48 out of 10. Furthermore, 68.75% of policies (11 out of 16) reached the ‘excellent’ level (PMC ≥ 8.0), with Policy “P6” achieving the highest score of 8.88 points. Top-performing policies exhibited strong strategic coordination, clear objectives, and comprehensive supporting measures. The findings reveal a well-structured policy cluster with clear objectives and strong coordination. This mature policy package provides a solid institutional foundation for China’s energy system transformation toward smart and green development, offering valuable insights for energy policy optimization and quantitative assessment methodology improvement.

Objective: To evaluate the impact of urban–rural health insurance integration on the health outcomes and financial burden of rural older adults. Methods: Utilizing panel data from the China Health and Retirement Longitudinal Study (CHARLS) spanning 2013 to 2018, we employed a staggered difference-in-differences model coupled with propensity score matching (PSM-DID) for rigorous causal identification. Results: The policy significantly reduced out-of-pocket medical expenditures for rural households by approximately 5.6% (p = 0.034). Concurrently, significant improvements were observed in both physical health (a 0.092-point reduction in ADL impairment scores) and mental health (a 0.725-point reduction in CES-D depression scores). Mechanism analyses revealed that the integration did not significantly increase the probability of outpatient or inpatient visits—thereby ruling out supplier-induced demand and moral hazard—while effectively reducing the incidence of catastrophic health expenditure by 1.9% (p = 0.004). Heterogeneity analyses indicated that while the financial relief was universally distributed across varying educational levels, the policy dividends were predominantly captured by the younger-old demographic. Notably, the reduction in financial burden was not statistically significant for the oldest-old cohort (aged 75 and older). Conclusions: The urban–rural health insurance integration has achieved a dual dividend of financial protection and health enhancement without triggering the overutilization of medical services. Nevertheless, the unmet care expenses for older adults with severe disabilities underscore the urgent necessity for a secondary safety net, such as long-term care insurance.

Carbon abatement research is dedicated to exploring and evaluating strategies and technologies to reduce atmospheric carbon dioxide concentrations to mitigate the effects of global climate change. Based on this, the article found through the econometric analysis of the core set of literature in the WOS database in the past 10 years that: firstly, carbon emission reduction research is in a period of development, forming a core journal with SCI TOTAL ENVIRON, Journal of Cleaner Production, etc., a core research team with Cai, Bofeng, Shan, Yuli, Dong, Feng, etc., and core countries with China, the United States, and the United Kingdom as the core issuing and research powers. Secondly, the five key areas of sustainable development, economic growth and consumption, energy efficiency, climate change, and energy consumption, and the three key areas of energy efficiency, climate change, and energy consumption, have been discussed in this study. Thirdly, there are five themes of sustainable development, economic growth and consumption, energy efficiency, climate change and drivers, and energy consumption. From these, nine research details, such as carbon emission measurement and monitoring, carbon emission reduction technology research, carbon emission reduction policy and management, energy efficiency, and clean energy development, carbon emission trading market, carbon emission efficiency and environmental policy research, data-driven economics and environmental analysis, climate change, carbon emission drivers, and so on are extended. Finally, the analysis of the evolutionary process has undergone three stages: exploration of basic theories, application of specific industries and policy interventions, and integration of carbon emission reduction targets into socio-economic development plans. Carbon emission and sustainable development research, carbon emission reduction, and energy efficiency improvement are the latest frontiers of carbon emission reduction research.

Urban flood resilience depends not only on the scale of infrastructure investment, but also on whether such investment can be translated into observable flood-mitigation outcomes. Focusing on the transformation from infrastructure response to flood outcomes, this study uses panel data for 21 prefecture-level cities in Guangdong Province from 2016 to 2022. Annual maximum monthly precipitation is used to represent rainfall pressure, stormwater pipe density to represent infrastructure scale, and the number of reported flood events to represent the outcome variable. A two-way fixed-effects Poisson pseudo-maximum likelihood (PPML) model is employed. The results show that, in the full sample, rainfall pressure is positively, but not significantly, associated with reported flood occurrence, while stormwater pipe density does not exhibit a stable negative moderating effect. The main conclusion remains broadly unchanged when alternative outcome and precipitation indicators are used, when pipe density is lagged by one period, and when a conservative sample is adopted. Extended analysis provides only limited weak negative evidence for Pearl River Delta cities, and this evidence is not robust across alternative specifications. The findings indicate that pipe length per unit of built-up area primarily reflects the scale of infrastructure provision and cannot be directly equated with the operational performance of the drainage system. By separating response inputs from outcome performance, this study reveals the conditional nature of the transformation from infrastructure scale to operational performance in urban flood resilience research and provides empirical support for a shift from infrastructure expansion toward performance-oriented and integrated governance in high-density coastal cities.

The Guangdong–Hong Kong–Macao Greater Bay Area has high building density and diverse project types, and building disaster governance features cross-regional, multi-stakeholder and strongly uncertain characteristics. To reveal the multi-agent strategic interactions after embedding AI digital technologies into the governance process, this paper constructs a three-party stochastic evolutionary game model among public regulators, construction firms and AI technology providers, and introduces multiplicative Gaussian white noise with boundary degradation into the replicator dynamics. The study finds that (1) under baseline parameters, the system evolves toward the state “coordinated strong regulation–AI-compliant governance–high-quality supply”; noise below the local mean-square stability threshold does not change the direction of recovery near the equilibrium but enlarges short-term fluctuations of stochastic trajectories; (2) there is synergistic transmission in the initial strategies of the three parties, with firms’ compliance probability linking both the regulatory and technology sides; (3) governance performance benefits, cross-regional coordination gains, firms’ digitalization gains and high-quality technology subsidies each form positive incentives at different links, while firms’ AI retrofit costs directly depress compliance returns; (4) the mechanism shown on the original parameter surface indicates that higher AI retrofit costs first suppress firms’ AI-compliant governance and, via firms’ demand transmission, affect high-quality technology supply, whereas the response of public regulators is relatively weak. The findings provide mechanism-level hypotheses for phased incentives, cross jurisdictional data collaboration, technology quality assurance, and adaptive regulation. Because the parameters are dimensionless and uncalibrated, project or jurisdiction specific policy magnitudes require empirical estimation and validation.