As a new factor of production, data play a key role in driving low-carbon and sustainable development relying on the digital economy. However, previous studies have ignored this point. Based on the panel data of 283 cities in China from 2007 to 2019, we investigated the construction of national big data comprehensive pilot zones (NBDCPZs) in China as a quasi-natural experiment, using the difference-in-differences (DID) model to empirically test the impact of NBDCPZ policies on urban low-carbon transformation. The following conclusions can be drawn: NBDCPZ construction significantly promotes urban low-carbon transformation, and a series of robustness analysis supports this conclusion. NBDCPZ constructions mainly promotes urban low-carbon transformation by stimulating urban green innovation and optimizing the allocation of urban resource elements. Compared with eastern cities, small and medium-sized cities, and resource-based cities, the construction of NBDCPZs can promote the low-carbon transformation of cities in central and western China, large cities, and non-resource-based cities. Further analysis shows that the construction of NBDCPZs can only improve the low-carbon transformation of local cities, with negative spatial spillover effects on the low-carbon transformation of surrounding cities. Therefore, in the future, it is vital to consider the promotion effect of the construction of NBDCPZs on the low-carbon transformation of local cities and prevent its negative impact on the low-carbon transformation of surrounding cities.

Improving the low-carbon utilization efficiency of urban land is crucial to the low-carbon transformation and sustainable development of China and the world economy. Innovation-driven development, especially the construction of National Independent Innovation Demonstration Zones (NIIDZs), is an important measure to realize the low-carbon transformation of urban land use and sustainable economic development in China. However, previous studies have neglected to study the impact of the construction of NIIDZs on the low-carbon utilization efficiency of urban land. Based on a theoretical analysis and using the panel data of 283 cities in China from 2006 to 2019, we took NIIDZ construction in China as a quasi-natural experiment and adopted the progressive difference-in-differences method (DID) to evaluate the impact and action mechanism of NIIDZ construction on urban land low-carbon utilization efficiency. We found that NIIDZ construction can significantly promote the improvement of the low-carbon utilization efficiency of urban land, and a series of robustness analysis results support this research conclusion. With the passage of time, this kind of promotion effect shows a trend of increasing fluctuation. NIIDZ construction mainly improves the low-carbon utilization efficiency of urban land by promoting green technology innovation and generating economies of scale. In addition, compared with eastern cities, small-scale cities and resource-based cities, the promotion effect of NIIDZ construction in central and western cities, large cities, and non-resource-based cities is more obvious. This study provides a theoretical basis and practical reference for the low-carbon utilization of urban land from the perspective of innovation in China.

The digital transformation of enterprises is a significant catalyst for achieving cleaner production and directly affects a company’s carbon performance. This research elucidates the theoretical logic and potential impact mechanisms of digital transformation in reducing corporate carbon emissions. Second, using a panel data set of Chinese A-share listed companies from 2007 to 2020, this study quantitatively investigates the effect of corporate digital transformation on the carbon emissions intensity of businesses. The empirical results indicate that corporate digital transformation has a statistically significant negative effect on the carbon emissions intensity of Chinese firms. Several robustness tests have validated this conclusion. The heterogeneity analysis reveals that state-owned businesses, firms with high carbon intensity, and those with strong financing capacity would benefit more from digital transformation in achieving the goal of reducing carbon emissions. Furthermore, the impact of digital transformation on corporate carbon emission abatement is more prominent in industries with limited technological input and high energy consumption. At the regional level, digital transformation has a more significant impact on reducing carbon emissions in cities with stringent environmental regulation, advanced marketization, and resource-based economies. The transmission mechanism analysis confirms that improving corporate energy use efficiency, enhancing financial performance, and fostering green innovation are crucial transmission mechanisms through which digital transformation can help enterprises decrease their carbon emissions. These findings assist companies in comprehending the role of digital transformation in lowering carbon emissions and provide them with valuable insights.

Territorial space is a multi-functional complex. The coordinated production-living-ecological space (PLES) effectively coordinates the man-land relationship, promotes regional sustainable development, and maximizes territorial space. How to build a high-quality national spatial layout and support system for development has become a hot topic of concern in all sectors of society. However, few studies have explored the coupling coordination considering the various production-living-ecological functions of land use type and its influencing factors of PLES at the county scale in China. To address the gap, based on the connotation of PLES theory, this study established a classification and evaluation system for PLES and analyzed the spatio-temporal characteristics, coupling coordination degree, spatial autocorrelation, and influencing factors of PLES in China from 2000 to 2020. The results are as follows: (1) The production space index and living space index in China showed a continuous increase tendency, while the ecological space index decreased continuously during the study period. The production space and living space were concentrated in the east of Hu Line, and the ecological space indexes in mountainous areas were significantly higher than those in plain areas during the study period. (2) The gravity centers of PLES all migrated to the west of China to different degrees during the study period. (3) From 2000 to 2020, the basically balanced category was the main coupling coordination type, and the number of seriously unbalanced categories accounted for the least. In the west of the Hu Line, the seriously unbalanced category was dominant, while in the east of the Hu Line were the moderately unbalanced categories and above. (4) During the study period, the low-low type was the main relationship type, widely distributed in western China, followed by the high-high type, mainly situated in the North China Plain, Yangtze River Delta, Pearl River Delta, Jianghan Plain, Chengdu Plain, Northeast China Plain, and some provincial capital cities. (5) Regression results showed that natural factors were the main reason restricting the coordinated development of PLES, and socioeconomic factors could effectively promote the coordinated development of PLES. Landscape pattern also significantly influenced the coordinated development of PLES, but varied greatly. The findings of this study can provide a scientific reference for the optimization of territorial space layout and the promotion of high-quality development of territorial space.

Against the background of global climate change and the rapid rise of the digital economy, the digital transformation of agriculture is profoundly changing the agricultural production and operation mode with the help of digital technology, becoming a new driving force for low-carbon and sustainable development of agriculture. However, previous studies rarely examined the impact of agricultural digital transformation on agricultural low-carbon transformation from the perspective of carbon productivity. To fill this gap, this study attempts to build a theoretical analysis framework for the impact of agricultural digital transformation on agricultural carbon productivity (ACP). By using a set of panel data from 30 provinces (cities) in China from 2011 to 2019, this study explores the impact of agricultural digital transformation on ACP, as well as its conduction mechanism and the non-linear mechanism. Empirical results show that the transformation of agricultural digitalization is conducive to the promotion of ACP. A series of robustness analyses support this conclusion. The main transmission mechanisms for digital transformation to affect ACP include agricultural industrial structure upgrading, and the agricultural scale operation. In addition, with the improvement of urbanization level and rural human capital, the impact of agricultural digital transformation on ACP presents a “U” type non-linear feature of inhibition first and promotion later. Furtherly, heterogeneity analysis shows that the impact of digital transformation on ACP will vary greatly depending on the levels of ACP, the geographical location of the studied area and whether it is a main grain-producing area. This study provides a theoretical and empirical basis for the improvement of China’s agricultural carbon productivity from the perspective of the digital economy.