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China's crude economic development has led to high pollution and inefficiency of urban land use. Environmental regulation (Er) is crucial for governments to promote green growth and efficient land use. Using a dataset of 271 cities in China from 2011 to 2020, this paper investigates the threshold effect of green innovation in science and technology and industrial structure optimization on Er impacts of urban land green use efficiency (Ulee). The results show that (1) Er positively affects Ulee. (2) There is a threshold effect of green innovation in science and technology (Gin) and industrial structure upgrading (Ind) in Er affecting Ulee, and the force decreases as the threshold value increases. (3) Within the examination of heterogeneity, the impact of Er on Ulee is more significant in eastern, high levels of urbanization and large cities, but the force of action is smaller. Based on the nonlinear force of Er, it is crucial to maximize the effectiveness of green land use by giving full play to the interactive synergistic effect of the ''combination box'' and dynamically and flexibly adjusting the intensity of Er according to the time, place, and state of urban development.

To realize the development goals of environmental governance and low-carbon emission reduction, the effect of local environmental protection fiscal expenditure on carbon emissions needs to be assessed. This paper utilizes the panel data of 30 provinces in mainland China except Tibet from 2007 to 2019 and empirically examines the baseline effect, the mechanism, the nonlinear effect, and the spatial spillover effect of the local environmental protection fiscal expenditures affecting the intensity of carbon emissions by using the fixed-effects model, the FGLS model, the threshold panel model, and the spatial Durbin model. The results indicate that local environmental fiscal expenditure significantly lowers carbon emissions, generating a carbon reduction effect, and this finding remains robust under various checks; the mechanism analysis reveals that local environmental fiscal expenditure facilitates industrial structure upgrading, thereby indirectly producing a carbon reduction effect; the threshold analysis shows that the carbon reduction effect of local environmental fiscal expenditure exhibits a diminishing marginal tendency, and as the industrial structure continues to upgrade, the carbon reduction effect of local environmental fiscal expenditure displays an “Inverted U-shaped” pattern; the spatial analysis demonstrates that local environmental fiscal expenditure and carbon emissions have positive spatial autocorrelation, and local environmental fiscal expenditure in one region will induce a decline in carbon emissions in neighboring regions through spatial spillover effect. Based on the above results, this paper puts forward policy suggestions in terms of constructing a reasonable growth mechanism for local environmental protection financial expenditures, creating an ecological environment for low-carbon transformation, and constructing a reasonable regional coordination mechanism for carbon emission reduction.

The iterative upgrading of digital technology and the implementation of “carbon-peaking and carbon neutrality” national strategy provide an opportunity for the synergistic integration of digital economy and green economy in China, thus, whether the development of digital economy can curb urban carbon emission intensity (CEI) remains to be answered. Based on the panel data of 110 cities in the Yangtze River Economic Belt (YREB) region from 2011 to 2020, this paper investigated the impact of digital economy on CEI by using the dual fixed-effect model, the mediating mechanism model and the spatial Durbin model. The main results are as follows: (1) The development of digital economy in the YREB region can lower down CEI, promote the rationalization and upgrading of industrial structure, and improve cities’ green innovation capacity; (2) CEI was reduced through the intermediary effect of industrial structure optimization and upgrading and green technology innovation; (3) Digital economy shows a significant positive spatial correlation, and exerts a spatial spillover effect of reducing CEI in surrounding cities with obvious spatial heterogeneity; (4) Digital economy has a stronger inhibitory impact on CEI in the downstream cities and cities within the urban agglomerations; (5) In addition to digital infrastructure, the remaining components of digital economy, directly and indirectly, diminish CEI. At last, according to the research findings, suggestions for digital economy development in the YREB region are put forward.

Nowadays countries in the world are striving to transform their economic and social development modes to achieve the general goal of green development. With the rapid development of communication technology, digitalization has affected production and life, touching all aspects of society. Can digitalization make the world “greener”? To this end, this study conducts an empirical research based on the panel data of 276 cities in China from 2011 to 2020. Firstly, this paper separately measured the comprehensive level of urban digitalization and urban greening through the Entropy-TOPSIS method, then analyzed their spatial distribution characteristics and evolution process respectively, finally used the spatial Durbin model to explore the impact of digitalization on urban greening development. The following conclusions were drawn accordingly: (1). The development pattern of urban digitalization has changed from “multi-point” sporadic distribution to “group-type” aggregation with obvious spatial heterogeneity. The gap between cities is not narrowing. The Yangtze River Delta urban agglomeration has become an important high-level digital agglomeration area; (2). The urban greening develops with obvious spatial heterogeneity. The difference between eastern regions and western regions is prominent, and the urban spatial agglomeration characteristic is distinct. However, the spillover effect is weakened with distance, while the convergence characteristic becomes obvious; (3). Digitalization is significantly beneficial to the development of urban greening with obvious spatial heterogeneity. Digitalization in cities within urban agglomeration and in eastern regions has a stronger effect on promoting the urban greening, which is not obvious in cities located in western regions and non-urban agglomeration. Finally, according to the research results, suggestions for urban digitalization and greening development are put forward.

As China's urbanization accelerates, ecological environmental issues have become increasingly prominent, and how to achieve the synergistic development of urbanization and ecological environment is worth exploring. The paper uses the Super-SBM model and the improved entropy method to calculate the ecological efficiency and the new urbanization in 63 counties in Zhejiang Province from 2000 to 2019. Furthermore, the coupling coordination degree between new urbanization and ecological efficiency is discussed with the coupling degree model, Markov chain, and spatial correlation methods, and its influencing factors are explored by the geographic detector. The results show that: (1) The development trends of new urbanization and ecological efficiency in Zhejiang Province counties both present a "U" shape. Their inflection points appeared in 2005 and 2006, respectively. The gap between counties is gradually narrowing. (2) The coupling coordination degree between new urbanization and ecological efficiency in Zhejiang Province counties also develops in a "U" shape with the minimum value appearing in 2006. Its temporal evolution is dominated by advancement towards a higher level and maintenance of the original type, with most countries advancing from General Disorder to Preliminary Coordination. There is a good positive correlation in the spatial distribution, showing significant High-High and Low-Low agglomeration. (3) In detecting the driving factors, the explanatory power of economic development, natural conditions and social conditions diminishes sequentially. The interaction groups mostly are nonlinear enhancements, and the rest are all two-factor enhancements. Social factors are the main interaction objects. (4) The empirical analysis verified the efficacy of the "Two Mountains" theory and the importance of government investment in the regional coordinated development.