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.

In this study, we calculate the urban land green use efficiency (ULGUE) in the Yangtze River Economic Belt from 2005 to 2019 by using the epsilon-based measure (EBM) model. Further, the spatial-temporal distribution, regional differences and evolution trends of ULGUE in the Yangtze River Economic Belt are investigated in depth by using the Dagum Gini coefficient, Kernel Density estimation and Markov Chain method. The following results are obtained. 1) From the perspective of spatial-temporal evolution, the ULGUE in the Yangtze River Economic Belt show a fluctuating upward trend from 2005 to 2019, and it is manifested as diffusion from downstream to middle and upper reaches. 2) From the perspective of regional differences, there is a relatively obvious imbalance of ULGUE within the Yangtze River Economic Belt, but the differences narrow over time. 3) Considering the distribution dynamic evolution, the box diagram and distribution curve of ULGUE in the Yangtze River Economic Belt have a tendency to move to high values, but there is a more obvious phenomenon of spatial polarization. 4) For the part of time and space transfer, the ULGUE within the Yangtze River Economic Belt show the characteristic of “club convergence”, and the Spatial Markov Chain results show an obvious “spatial spillover” effect.

Existing research lacks a systematic and comprehensive analysis of the digital economy (DE)’s impact on the low-carbon transformation of resource-based cities. This study utilizes panel data from 114 of these cities in China from 2006 to 2019 to construct a DE measurement system. Based on the global SBM directional distance function and the Malmquist–Luenberger index (SBM-DDF-GML), we calculated the total factor carbon productivity (TFCP), decomposed the carbon inefficiency value (CIV), and examined DE’s impact, mechanism, and heterogeneity on low-carbon transition development (LCTD) during distinct growth phases of resource-based cities. Based on this examination, we found the following: (1) The DE effectively reduced carbon intensity and inefficiency and improved the total factor carbon productivity in resource-based cities. These findings remained robust after a series of robustness tests. (2) The DE empowered LCTD by improving energy efficiency, upgrading industrial structure, and optimizing innovation factor allocation. Finally, (3) this effect varied across the different city stages, being most significant in mature cities and weakest in declining ones. The research findings provide empirical evidence for the LCTD of resource-based cities.

Urban agglomerations (UAs) are the main battlefield of urbanization and the most concentrated areas of carbon emissions (CEs). Nevertheless, limited studies have examined the impact of urbanization level (UL) on CEs in UAs in China. This study aimed to identify the spatial relationship between UL and CEs in Chinese UAs and to conduct a comprehensive analysis of the differences in CEs caused by urbanization. The findings would provide scientific support for the China’s dual-carbon goals and the achievement of green and low-carbon urban development. Spatial variations in UL and CEs in 19 Chinese UAs were assessed in 2000, 2010, and 2020 using distribution dynamics and spatial regression models. The results indicated that the UL of UAs in China evidently increased over time, and UAs contributed approximately 80% of the national CEs. Significant spatial dependence was identified between urbanization factors and CEs. The regression results indicated that an increase in UL promoted the growth of CEs, and the form of the urban land had a significant and highly variable impact on CEs. Our findings provide a valuable case study for exploring relationships between UL and CEs in other UAs worldwide.