Shouhong Xie

China’s traditional agriculture has grown quickly but at the cost of excessive pollution and energy consumption. Therefore, low-carbon development in agriculture is crucial to achieving “carbon neutrality” and “carbon peaking.” With the development of China’s digital economy and the construction of digital villages in recent years, digital technology innovation (DTI) is probably going to a significant role in lowering agricultural carbon emissions (ACEs). Based on Chinese provincial panel data from 2006 to 2021, we analyze the spatial and temporal evolution characteristics of DTI and ACE, explore the impact and the pathways of DTI on ACE using a spatial econometric model, and reveal this impact’s heterogeneity and nonlinear character. The findings show that DTI and ACE increased significantly throughout all Chinese provinces. DTI agglomeration is becoming stronger, whereas ACE displays a tendency for discontinuous distribution. DTI is essential in promoting low-carbon development in agriculture, and there are significant spatial spillover effects due to technology spillovers. Heterogeneity analysis indicates that DTI has positive impacts on local agriculture in different regions. However, there is variation in the impact’s degree. The mechanism test’s findings show how DTI reduces ACE by improving technology and enhancing resource endowment. The relationship between DTI and ACE exhibits an inverted “U” curve, and the level of economic development is the threshold variable that constrains the relationship between the two variables. To achieve a regional balanced low-carbon development in agriculture through DTI, it is important to emphasize the impact of DTI on reducing carbon emissions and to encourage the transfer of mature technology from high-level regions to low-level regions.

The distribution and evolution of city size are critical for town layout optimization. Based on the most recent classification standards and census data for 2010 and 2020, this paper aims to explore China’s city size distribution above the prefecture level. Using the rank-size law, Kernel density estimation, Spatial Gini coefficient, and Markov transition matrix, the newest city size distribution characteristics and spatial evolution patterns in China are shown from national and regional viewpoints. Our main findings are as follows: (1) Over the period from 2010 to 2020, China’s city size distribution follows the rank-size law but deviates from Zipf’s ideal. The distribution of city size is centralized in general. (2) China’s city-size hierarchy exhibits a good “olive” structure, with fewer megacities but larger populations. The growth rate of small and medium-sized cities is higher than the number of medium-sized cities. (3) China’s cities have grown greatly in size, with more than a third of them expanding. Over the last decade, high-ranking cities have become the primary driver of change. (4) There are disparities in city size between regions. A diminishing trend can be seen in three key economic zones.

Spatial agglomeration, as a phenomenon of commodity trading markets, reflects regional economic development in China. This study explores the spatial agglomeration of commodity trading markets and analyzes its influencing factors. Based on the panel data of 30 provinces in China from 2010 to 2019, this article first calculated the location quotient of the transaction volume of commodity trading markets and analyzed their temporal and spatial trends. Finally, a spatial econometric model was used to conduct an empirical examination of the influencing factors determining the spatial agglomeration of commodity trading markets. The results show that the agglomeration pattern of China’s commodity trading markets has changed significantly from 2010 to 2019. In terms of geographic variations, we discovered that the eastern region has a higher degree of commodity trading market concentration than the central and western regions. In terms of influencing factors, this study found that the level of economic development, the degree of openness, and the development of private industrial enterprises still positively affect the spatial agglomeration of commodity trading markets. However, the level of social consumption has no significant impact. Based on these findings, this article puts forward relevant policy recommendations to promote the further development of China’s commodity exchange market.