Climate change is one of the most urgent challenges facing the world. All countries should take joint actions to achieve the goal of carbon neutrality, which include controlling global warming to within a 1.5 °C temperature rise, to mitigate the extreme harm caused by climate change. However, ways in which to achieve economically and environmentally sustainable carbon neutrality are yet to be established. Carbon neutrality appears frequently in international policy and the scientific literature, but there is little detailed literature. It is necessary to conduct an in-depth analysis of the development context of its research. This paper analyzed the literature on carbon neutrality using bibliometric methods. A total of 1383 research papers were collected from the “Web of Science core database” from 1995 to 2021. Descriptive statistical analysis and keyword co-occurrence and literature co-citation network analyses were utilized to sort the research hotspots, and the detected bursts, the top 30 keywords in terms of word frequency, and 12 clusters were selected. It was found that the existing carbon neutrality research literature mainly focuses on carbon neutrality energy transformation, carbon neutrality technology development, carbon neutrality effect evaluation, and carbon neutrality industry examples. The analysis process involved comprehensively reading the key articles and considering the co-citation, burstiness, centrality, and other indicators under clustering; the carbon neutrality research was then divided into three stages, and evolving themes were observed. Based on the burst detection, this paper holds that with the energy structure transformation, energy consumption assessment and carbon neutrality schemes of various industries, carbon dioxide capture technology, and biogas resource utilization, urban carbon neutrality policy will become a research hotspot in the future. This paper helps to provide a reference for scholars’ theoretical research and has important reference value for policymakers to formulate relevant policy measures. It is helpful for enterprises to make strategic decisions and determine the direction of technology, for R&D and investment, and it is of considerable significance to promote the research of carbon neutrality technology.

Flash floods are devastating natural disasters worldwide. Understanding their spatiotemporal distributions and driving factors is essential for identifying high risk areas and predicting hydrological conditions. In this study, several methods were used to analyze the changing patterns and driving factors of flash floods in the Altay region. Results indicate that the number of flash floods each year increased in 1980–2015, with two sudden change points (1996 and 2008), and April, June, and July presented the highest frequency of events. Habahe and Jeminay were known to have high flash flood incidences; however, currently, Altay City, Fuhai, Fuyun, and Qinghe are most affected. In terms of driving force analysis, precipitation and altitude performance have a key impact on flash flood occurrence in this settlement compared to other subregions, with a high percentage increase in the mean squared error value of 39, 37, 37, 37, and 33 for 10 min precipitation in a 20-year return period, elevation, 60 min precipitation in a 20-year return period, 6 h precipitation in a 20-year return period, and 24 h precipitation in a 20-year return period, respectively. The study results provide insights into spatial–temporal dynamics of flash floods and a scientific basis for policymakers to set improvement targets in specific areas.

This paper uses CiteSpace software to conduct a bibliometric analysis of research literature under the topic of game theory which specifically focuses on energy and natural resources in the Web of Science Core Collection. The results show that: since 1990, the number of documents covering the topics of “energy” and “game theory”, and “natural resources” and “game theory” has continued to grow steadily, and entered an explosive growth stage after 2017. In terms of disciplinary classification of published papers, Energy & Fuels has the highest frequency, 311 with a significant centrality, 0.22. In terms of journal publications, Applied Energy is the most cited journal whose frequency is 311 and centrality is 0.01. In terms of country, China has the highest number of published papers, and the United States with the highest overall centrality of papers. North China Electric Power University published 31 papers, the largest number of documents from one institution. In terms of author productivity, Puyan Nie has been the most productive author since 2016. The co-citation cluster analysis on the literature topics shows that the game theory of energy and natural resources have roughly gone through four stages: (1) From 1990 to 2009, this is the embryonic stage with no more than 15 new papers per year; (2) From 2010 to 2014, this stage had microgrid as its mainstream research topic, and other topic clusters officially emerged; (3) From 2015 to 2017, the main research topics became the integrated energy system, subsidy mechanism and household energy management, with a hot topic on the evolutionary game process between government and enterprises; (4) From 2018 to 2021, this stage continued to focus on the previous topics, and the research goes much deeper, resulting in more models and new green technologies. Finally, the keyword analysis concludes with nine themes of concern in this research field, and has come to a comprehensive summary of the mainstream research methods in the field of game theory of energy and natural resources.

Amidst escalating global policy uncertainties and the painful transformation phase of the Chinese economy, studying the time-varying characteristics of risk spillover among the real economy, real estate market, and financial system holds substantial practical relevance for preventing and resolving significant systemic risks. This paper employs the TVP-VAR-DY model, selects indices from the real sectors to construct a risk spillover index for the real economy, and incorporates indices from the real estate and financial sectors to develop a trivariate SV-TVP-VAR model for empirically analyzing the time-varying nature of risk spillover relationships among these variables. This study reveals that risk spillover among different sectors of the real economy exhibits asymmetry and volatility, with the industrial sector experiencing the highest degree of risk spillover. The prosperity of the real estate market consistently aligns with that of the financial system; however, shocks during periods of risk accumulation in the real estate market significantly amplify risks in the real economy. The financial system serves the real economy, which suffers lesser impacts. Nonetheless, post-2008, the financial system’s support for the real estate market has gradually diminished. Crises exacerbate the extent of risk spillover, but the causative factors and socio-economic context create heterogeneity in fluctuations. Based on these findings, in response to the current real estate shock, the Chinese government should discuss the real economy, the real estate industry, and the financial system within the same research framework. Policies should primarily focus on fiscal measures to promote the recovery of the real economy more rapidly. Additionally, by allowing local governments to implement tailored policies based on local conditions, potential homebuying demand has been effectively stimulated.

With China’s rapid industrialization and urbanization, sustainable urban development is one of the most significant challenges that the country will face in the future, and the rational evaluation and improvement of urban land-use efficiency (ULUE) are becoming crucial for land and urban development. Existing studies rarely examine ULUE, and there is a dearth of urban land use analysis in terms of different functions, regional differences in levels of development, and innovation capacity. Therefore, we take the Pearl River Delta (PRD), China’s economic and innovation center, as our research target and propose a new framework to analyze its comprehensive ULUE. First, we summarized the patterns of land-use change in the PRD region as a whole along with nine major cities from 2000 to 2020 on the basis of data from the China Land Survey. Then, we constructed a multidimensional evaluation model for ULUE and analyzed the spatial differences and causes of multidimensional performance in nine major cities. Finally, we calculated the innovation capability index of the PRD region and established a coupling coordination–evaluation model to analyze the coordination relationship between innovation capability and urban land use. The three main findings of this study are as follows. (1) The growth rate of urban land in the PRD region as a whole exhibited stage differences. (2) The comprehensive ULUE in the PRD urban agglomeration was high, and the spatial variability of functional performance in each dimension was obvious. (3) The level of coordination between innovation capability and urban land use in the PRD region was high, and the coupled coordinated development exhibited a decreasing spatial distribution pattern. Thus, the PRD region mainly relies on the cities of Shenzhen and Guangzhou to drive innovation development of the region.

Ecologically fragile areas in China account for more than half of its land area. Performing early warning assessments and trend analyses of resource and environment carrying capacity in ecologically fragile areas can lay a scientific foundation for ecological conservation in the areas. Based on the connotation of resource and environment carrying capacity, an early warning index system of resource and environment carrying capacity in Altay prefecture was constructed from the three aspects natural resource carrying capacity, eco-environment carrying capacity, and economic and social support capacity. The grey relational projection method model was used to analyze the current alarm situation of the resource and environment carrying capacity in Altay prefecture from 2011 to 2020, and then the back propagation (BP) neural network and a mathematical statistics software were used to predict the evolution of the alarm situation of the resource and environment carrying capacity in Altay prefecture from 2021 to 2025. The results demonstrated that (1) the natural resource carrying capacity subsystem was the main system of the development of the resource and environment carrying capacity in Altay prefecture, and its impact on the resource and environment carrying capacity in Altay prefecture was greater than the eco-environment carrying capacity and economic and social support capacity; (2) the resource and environmental carrying capacity of Altay prefecture showed a slight upward trend from 2011 to 2020, although the range was constrained and the level of warning remained “moderate warning”. A spatial pattern of “weak in the middle, strong in the two poles” was exhibited by the warning scenario about the carrying capacity of each county and city. Except for the warning of Habahe County and Qinghe County, where the warning was slightly worse than that in 2020, the warning of resource and environment carrying capacity in Altay prefecture and other counties and cities would show a trend of fluctuation and decline from 2021 to 2025. However, the degree of alarm did not change substantially and remained at the level of “moderate warning”; (3) the main factors restricting the mitigation of the warning of resource and environment carrying capacity in Altay prefecture included a low soil fertility index, a small total reservoir capacity, low per capita mineral resource reserves, a low water resource development and utilization rate, a low comprehensive utilization rate of industrial solid waste, and a low land output rate.