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The unavoidable option for socially sustainable development is a low-carbon economy. One of the essential steps for China to attain high-quality development is reducing carbon emissions. It is necessary to realize low-carbon development in Sichuan, as it is not only an important economic zone but also an ecological protected area. The concurrent relationship among energy consumption, carbon emissions, and economic growth was examined in this study using the Tapio decoupling indicator, and the factors affecting energy consumption and carbon emissions in Sichuan were broken down using the logarithmic mean Divisia indicator (LMDI). The findings demonstrate a fundamental relative decoupling relationship between Sichuan's energy use and carbon emissions. Analysis of energy consumption and carbon emissions in Sichuan Province from 2005 to 2020 shows distinct patterns. From 2005 to 2012, in 2014, and from 2016 to 2020, the relationship between energy use and carbon emissions was relatively decoupled, with decoupling values ranging between 0 and 1. Absolute decoupling occurred in specific years: 2010, from 2013 to 2018, and in 2020. These periods are characterized by economic growth alongside reductions in carbon emissions. Factors affecting energy consumption and carbon emissions were consistently analyzed, showing similar impacts throughout the study periods. We find that population and economic growth are the main driving forces of these effects. The effects of energy intensity and industrial structure mainly play restraining roles, and the latter has a slightly weaker effect than the former. [ABSTRACT FROM AUTHOR]

Using the digital economy to empower urban economic green growth provides essential opportunities for China to achieve high-quality growth. This paper assesses the level of digital economy and green growth in Chinese cities, seeking to explore the mechanisms and effects of the digital economy on urban green growth in a unified framework. The results indicate that the digital economy can drive cities' green growth. This conclusion still holds after a set of robustness tests. Meanwhile, the green value of the digital economy is fully released among the eastern cities, major urban agglomerations, and high-level cities. Further research shows that the digital economy can indirectly enhance urban green growth in the neighboring regions through spatial spillover effects. Moreover, labor resource mismatch, capital resource mismatch and green technology innovation are significant mediating mechanisms. The findings could guide policymakers on green growth in emerging economies from a digital economy perspective. [ABSTRACT FROM AUTHOR]

The 14th Five-Year Plan stated that China should accelerate green development and promote a comprehensive green transition in economic and social development. As China's economic growth slows, green development becomes greatly significant for the high-quality development of the economy. Based on China's provincial panel data from 2005 to 2021, this study applies fixed effects model and mediating effect model to explore the influence of the government environmental investment on green development. The results indicate that (1) the government environmental investment was conducive to green development, but such effect weakened with time. (2) The government environmental investment indirectly promoted green development through the application of green patents and economic agglomeration. (3) The promotional effect of the government environmental investment varied according to region and time. Specifically, investment exerted the most significant effect on the green development of eastern China, which became more evident after 2015. The government should promote green development by implementing long-term assessment and accountability mechanisms, expanding the scale of economic agglomeration, improving the efficiency of the application of green patents, and improving the accuracy of environmental investment. [ABSTRACT FROM AUTHOR]

The digital economy may accelerate the upgrading of industrial structures and boost regional innovation output, effectively contributing to China's green economic transformation. The impact of the digital economy on developing the urban green economy is analyzed using data from 280 cities across China from 2010–2019. Using a fixed-effects model and the Spatial Durbin model, the digital economy is found to have a significant impact on urban green economy development. This result is shown to be robust to various factors. There is significant regional variability in the impact of the digital economy on green economic growth, with the strongest impact in the northeast, followed by the central and western regions. Meanwhile, non-resource-based cities and policy pilot cities have a more pronounced role in promoting the digital economy. The intermediate transmission chain of industrial structural upgrading and regional innovation output fosters the growth of the urban green economy via the digital economy. Regional innovation production is responsible for 30.848% of this growth, with the intermediate effect of industrial structural upgrading contributing to 38.155%. [ABSTRACT FROM AUTHOR]

Using World Bank and IMF data over the period 1990–2018, this research explores the determinants of economic growth in Bangladesh with particular attention to environmental degradation and export concentration variables. An ARDL (Autoregressive Distributed Lag) bound testing approach is employed as an estimation strategy with FMOLS (Fully Modified Ordinary Least Squares) and CCR (Canonical Cointegrating Regression) for cross-checking the results. The obtained results confirm that CO2 emissions, consumption expenditure, export concentration, remittances, and inflation are the main driving forces for the long-run economic growth in Bangladesh where the effects of the first two variables and the last three variables are positive and negative, respectively. The study also reveals the dynamic short-run relationships among the chosen variables. Environmental pollution and export concentration are found to be the barriers to economic growth; therefore, the country should take necessary steps to mitigate this problem for ensuring long-run sustainable economic development. [ABSTRACT FROM AUTHOR]

Agriculture is the foundation of the national economy, and agricultural nonpoint source pollution and carbon emissions are the main environmental problems limiting the development of the agricultural economy. This study takes the Yangtze River Delta as the research object and measures agricultural carbon emissions and nonpoint source pollution in the study area from 2010 to 2020 respectively. The Tapio decoupling model is used to study types of decoupling between agricultural pollution and carbon reduction and economic growth in the Yangtze River Delta from 2010 to 2020, and the GM (1,1) model is used to predict the decoupling relationship between the agricultural environment and economic growth over the next ten years. The results show the following: (1) Agricultural COD emissions come mainly from livestock and poultry breeding, dropped from 1,130,120 tons in 2010 to 908,460 tons in 2020. Agricultural TN and TP emissions come mainly from plantations. Agricultural TN emissions dropped from 892,310 tons in 2010 to 788,020 tons in 2020. Agricultural TP emissions dropped from 149,590 tons in 2010 to130,770 tons in 2020. Agricultural carbon emissions dropped from 17,115,900 tons in 2010 to 15,786,600 tons in 2020, and come mainly from agricultural fertilizer and diesel fuel and pig breeding. (2) The decoupling effect of agricultural pollution reduction and carbon reduction in the Yangtze River Delta and economic growth has been in a long-term state, with negative decoupling occurring in a few regions, mainly in 2011, 2014 and 2020. (3) In the next ten years, except for 2021, when the coordination between agricultural pollution reduction and economic growth is poor, the two show good decoupling in the remaining years. Based on the results, this study makes recommendations on how to carry out comprehensive environmental management and promote green agricultural development. [ABSTRACT FROM AUTHOR]

In order to study the impact of inclusive finance on agricultural green development, This paper uses both static panel and dynamic panel (system GMM model) estimation methods to make empirical analysis of the impact of inclusive financial development on agricultural green development. The results both find that there is a significant positive correlation between the level of inclusive financial development, real GDP per capita, the proportion of the added value of agriculture, forestry, animal husbandry and fishery in GDP and agricultural green development. This paper puts forward some countermeasures and suggestions to promote agricultural green development, including vigorously developing inclusive finance, promoting economic growth, promoting the development of agriculture, forestry, animal husbandry and fishery, and increasing environmental protection expenditures. [ABSTRACT FROM AUTHOR]

Green development is an effective way to achieve economic growth and social development in a harmonious, sustainable, and efficient manner. Although the Yangtze River Economic Belt (YREB) plays an important strategic role in China, our understanding of its spatiotemporal characteristics, as well as the multiple factors affecting its green development level (GDL), remains limited. This study used the entropy weight method (EWM) to analyze the temporal evolution and spatial differentiation characteristics of the GDL in the YREB from 2011 to 2019. Further, fuzzy-set qualitative comparative analysis (fsQCA) was used to analyze the influence path of GDL. The results showed that the GDL of the YREB increased from 2015 to 2019, but the overall level was still not high, with high GDL mainly concentrated in the lower reaches. The GDL model changed from being environmentally driven and government supported in 2011 to being environmentally and economically driven since 2014. The core conditions for high GDL changed from economic development level (EDL) to scientific technological innovation level (STIL) and environmental regulation (ER). The path for improving GDL is as follows: In regions with high EDL, effective ER, moderate openness level (OL), and high STIL are the basis, supplemented by a reasonable urbanization scale (US). In areas with low EDL, reasonable industrial structure (IS) and STIL are the core conditions for development; further, EDL should be improved and effective ER and OL implemented. Alternatively, without considering changes to EDL, improvement can be achieved through reasonable OL and US or effective ER. This study provides a new method for exploring the path of GDL and a reference for governments to effectively adjust green development policies. [ABSTRACT FROM AUTHOR]

The green development of coastal urban agglomerations, which are strategic core areas of national economic growth in China, has become a major focus of both academics and government agencies. In this paper, China's coastal urban agglomeration is taken as the research area, aiming at the serious air pollution problem of coastal urban agglomeration, geographic information system (ArcGIS10.2) spatial analysis and the spatial Dubin model were applied to National Aeronautics and Space Administration atmospheric remote sensing image inversion fine particulate matter (PM2.5) data from 2010–2016 to reveal the temporal and spatial evolution characteristics and Influence mechanism of PM2.5 in China's coastal urban agglomerations, with a view to providing a reference value for coordinating air pollution in the coastal cities of the world. From 2010–2016, the PM2.5 concentration in China's coastal urban agglomerations decreased as a whole, and large spatial differences in PM2.5 concentration were observed in China's coastal urban agglomerations; the core high-pollution areas were the Beijing–Tianjin–Hebei, Shandong Peninsula, and Yangtze River Delta urban agglomerations. Large spatial differences in PM2.5 concentration were also observed within individual urban agglomerations, with higher PM2.5 concentrations found in the northern parts of the urban agglomerations. Significant spatial autocorrelation and spatial heterogeneity were observed among PM2.5-polluted cities in China's coastal urban agglomerations. The northern coastal urban agglomerations formed a relatively stable and continuous high-pollution zone. The spatial Dubin model was used to analyze the driving factors of PM2.5 pollution in coastal urban agglomerations. Together, meteorological, socioeconomic, pollution source, and ecological factors affected the spatial characteristics of PM2.5 pollution during the study period, and the overall effect was a mixed effect with significant spatial variation. Among them, meteorological factors were the greatest driver of PM2.5 pollution. In the short term, the rapid increase in population density, industrial emissions, industrial energy consumption, and total traffic emissions were the important driving factors of PM2.5 pollution in the coastal urban agglomerations of China. [ABSTRACT FROM AUTHOR]

This study analyses the impact of environmental and economic factors consolidation on sustainable entrepreneurship over time. A model is proposed that analyses the relations between these factors and sustainable entrepreneurship over time with sustainable development goals performances and the continuation of the businesses index as variables. Using data from 50 countries, a quantitative method based on partial least squares was applied to validate the proposed model. Our findings showed positive and significant relations between environmental and economic factors with sustainable entrepreneurship over time. This implies that the countries which invest more efforts to consolidate their economic and environmental factors obtain higher durability rates for their sustainable entrepreneurship. [ABSTRACT FROM AUTHOR]