China’s economy has developed rapidly since the reform and opening up, but under the long-term traditional extensive development model, energy consumption is excessive and carbon emissions rank first in the world. Therefore, how to reduce carbon emissions is a current hot issue in China. Although many scholars have found that green finance is the basic driving force to promote carbon emission reduction, its role path is diverse, and it still needs to be explored in width and depth. Especially in the green transformation stage of the economy, the potential unemployment risk is also a matter of concern. This study selects 30 provincial panel data from the Chinese mainland for the 2004–2019 years to investigate the impact of green finance on carbon emissions from the perspective of unemployment using ordinary least square (OLS), generalized method of moments (GMM), and mediating effect models. In addition, in order to avoid the bias of regression results caused by the cross-section dependence of the data, the feasible generalized least squares (FGLS) and the panel-corrected standard errors (PCSE) models are used for the robust test after correction. The findings show that 1) green finance has a significant inhibitory impact on carbon emissions; 2) green finance has significantly reduced the unemployment rate; 3) carbon emissions increase significantly with increasing the unemployment rate; and 4) there is regional heterogeneity in the effect of green finance on carbon emissions in eastern, central, and western China. Green finance in the eastern and central regions significantly inhibits carbon emissions, especially in the central region, while insignificantly in the western region. 5) According to the OLS and mediating effect regression results, economic growth and environmental regulation play a significant positive role in promoting carbon emissions. This study has theoretical reference significance for accelerating the realization of the dual carbon goal and alleviating phased unemployment.

The rapid growth experienced by the Gulf Council countries (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates) has placed significant strain on their ecological footprint due to extensive energy consumption. Consequently, it becomes necessary to examine the factors contributing to the high ecological footprint and explore potential solutions for its reduction. This study aims to analyze the key factors influencing the ecological footprint in the GCC countries from 1995 to 2020. Through an extensive review of existing literature, it is evident that economic growth, urbanization, and trade can disturb ecological balance, while environmental technology and renewable energy offer potential remedies for environmental challenges. Thus, these variables have been selected as independent factors for investigation. The results obtained from advanced panel techniques emphasize the significance of adopting environmental technologies and increasing the utilization of renewable energy sources in order to decrease the ecological footprint. Conversely, economic growth, urbanization, and trade are identified as crucial drivers of environmental degradation. Considering that the GCC countries heavily rely on oil and petroleum exports, as well as non-renewable energy sources for their economic activities, the positive relationship between economic growth and trade is to be expected. The results propose multifold recommendations: (i) providing incentives for renewable energy and (ii) prioritizing the implementation of clean technology over traditional technologies.

Implementing the rural revitalization strategy is crucial for ensuring and enhancing the livelihoods of the vast rural population. The upgrading of rural consumption reflects the gradual realization of rural residents’ pursuit of a better life, and the rapid development of digital inclusive finance provides strong support for this. Based on the Digital Inclusive Finance Index released by Peking University and panel data from 30 provinces across the country, this study examines the role of digital inclusive finance in optimizing rural consumption structure through the mediation effect model and analyzes its spatial spillover effects using the spatial Durbin model. The research shows that narrowing the development gap in digital inclusive finance is crucial for upgrading the rural consumption structure, which helps to promote rural residents’ transition to higher-level consumption. Through the analysis of the spatial Durbin model, this study finds spatial spillover effects in this process, meaning that financial development in a particular region promotes local development but inhibits development in neighboring areas. Among various dimensions, the impact of breadth of coverage is the most significant. This trend of financial development affects consumption structure by increasing agricultural productivity and rural residents’ operational income, particularly highlighting its impact on operational income. However, there are significant differences between the eastern and central-western regions in optimizing rural consumption structure, with the eastern region benefiting more while the effects in the central-western region are limited and sometimes even negative. Therefore, regional characteristics should be fully considered in policy formulation to narrow the development gap in digital inclusive finance and achieve high-quality and sustainable development.

This study employs panel data encompassing a time frame from 2012 to 2020, collected from 30 provinces in China. By employing a geographic Durbin model and introducing green technological innovation as an intermediary variable, the study explores the relationship between green funds and PM2.5 levels on a spatial scale. The research takes a spatial perspective to explore the links between green finance and PM2.5 emissions, with a specific focus on the intermediary role played by green technology innovation. The findings offer comprehensive insights into enhancing air quality in China, promoting the country's transition towards sustainability, improving the overall human living environment, and generating novel ideas for tackling air pollution challenges. The findings of this study are as follows: (1) The progress of green finance proves to be an effective means of reducing local PM2.5 emissions. Additionally, it generates spillover effects on neighboring regions, promoting the growth of green finance and consequently leading to a decrease in PM2.5 emissions in adjacent areas. (2) In the study exploring the relationship between green financing and PM2.5, green technological innovation plays a crucial mediating role. By efficiently allocating financial resources during China's pivotal green revolution phase, green finance offers funding support to enterprises for the advancement of green technology. This, in turn, contributes to the reduction of PM2.5 emissions. As a consequence, this leads to a decline in energy consumption, pollution emissions, and PM2.5 levels. Additionally, with the continuous improvement in green technological innovation, the reverse effect between green finance and PM2.5 is becoming stronger and stronger. (3) The relationship between the two has obvious regional heterogeneity between the north and south regions of China.

This study aims to examine the influence of environmental performance (PM2.5) on COVID-19 intensity . For this purpose, we employ the newly introduced Hidden Panel Cointegration test and Nonlinear Panel Autoregressive Distributed Lag model. Results indicate the asymmetric linkages between PM2.5 and COVID-19 intensity, as the positive shock in PM2.5 raises the COVID-19 intensity by 21%, whereas the negative shock in PM2.5 decreases COVID-19 intensity by 12% in long-run. On the contrary, the positive shock in stringency measures decreases COVID-19 intensity by 42.8%, while the negative shock in stringency policy increases COVID-19 intensity by 66.7%. These findings imply that higher pollution increases the COVID-19 severity while higher stringency measures slow down people’s movement and reduce COVID-19 intensity. However, a sudden negative shock in lockdown increases people’s interaction, leading to a higher spread of the virus. These results suggest that governments should adopt stringent action plans to contain the transmissibility of COVID-19.

The pig industry is primarily a domestic industry in China is focused on ensuring the domestic pork supply. This paper analyzed changes in Chinese pork imports following the outbreaks of African Swine Fever (ASF) and COVID-19 between January 2017 to November 2020 and evaluated the impact of imported pork on the development of the swine industry in China. The results demonstrated that the shortage of domestic pork supply changed the import volume. ASF transformed imported pork from a complementary product to meet the diversified needs of domestic consumers into a critical substitute required to fill the supply gap. Following the COVID-19 outbreak, the substitution effect of imported pork decreased. ASF, has caused the supply capacity of pork in China to decrease, the price of pork to increase, leading to increased pork import in January 2019. At the end of 2019, pig slaughter decreased, while China cut tariffs on imported pork. The COVID-19 outbreak did not reduce China's pork imports in China, which declined after the global COVID-19 outbreak. Imported pork has made up for the supply gap during COVID-19, not impacting the level of production of the swine industry in China.