The spatial autocorrelation analysis method was applied to panel data from the provinces of China (including autonomous regions and municipalities directly under the central government) for the period 2003 to 2016 in order to construct a spatial Durbin model of technological progress and financial support in relation to reductions in carbon emissions. The results show that China’s carbon intensity presents significant spatial spillover effects under different spatial weights, which indicates that the carbon intensity of a province is influenced not only by its own characteristics, but also by the carbon emission behaviors of geographically adjacent and economically similar provinces and regions. Financial structure, financial scale, and financial efficiency all have significant effects on carbon intensity within a province, while financial structure is also linked to carbon intensity in other regions, but financial scale has no significant spillover effect on carbon intensity in space. Areas with high financial efficiency can reduce their own carbon intensity as well as that of surrounding areas. The inter-regional spillover effect of technological progress on carbon intensity is stronger than the spillover effect, but there is a time lag.

Water shortages and pollution in China are severe situations caused by rapid economic development and urbanization. The current water-conservation policies focus on implementing new technologies and management strategies at important spatial nodes while neglecting the significance of the response from the community and the public. In this paper, the elements that influence the public participation of water conservation within the community are analyzed and divided into three levels: the internal world elements of the residents, the different individual characters of the residents, and external world elements. Among these three levels, the internal world element level, including the desire to realize oneself, is crucial, as it will significantly strengthen an individual's participation activity once motivated. Based on Maslow's five-level theory of human needs, to establish a model of public participation in water-conservation communities, economic benefits, environmental improvement benefits, and the self-fulfilling satisfaction of participation will become the motivation for the model to function. In a new project, reclaimed water landscapes are established in the community, and eco-recreational activities with water-conservation themes are organized to guide and encourage public participation to foster water-conservation consciousness and to establish aging water-conservation guiding policies and implementation methods in the community.

This paper uses Chinese provincial panel data from 2011 to 2019, measures CO2 emissions of provinces in China using the IPCC method, and explores the impact of digital finance on CO2 emissions through the SAR model and SDM. Empirical study shows that digital finance significantly reduces CO2 emissions. Digital finance reduces CO2 emissions by promoting energy industrial structure transformation and spreads to surrounding areas through spillover effects, contributes to increasing green patents granted and thus reduces regional CO2 emissions, advances the green technological progress and therefore inhibits CO2 emissions, but reduces the green technological progress in surrounding areas and increases CO2 emissions due to the siphon effect. With the development of digital finance itself, the higher the level of financial regulation, green development and the green finance index, the better the effect of digital finance on CO2 emission reduction. Additionally, digital finance significantly reduces CO2 emissions in the south of China.

The real estate market has been booming in China for the past 10 years. Highly leveraged on banks' credit, it has aroused regulators' attention because of the potential catastrophic consequence, and it may produce on the whole financial system if the housing price boom bursts and massive defaults on mortgages occur. In this article, reverse stress testing engineering has been employed to study the factors impacting significantly on the mortgages' defaults and their implicit transition mechanism under different simulated scenarios. This work, which produces more precise snapshots of the financial institutes' risk tolerances by pushing the risk factors to their limits, could be used by regulators for formulating housing price control policies and by banking management for implementing the credit default risk warning system.