Urban–rural integration (URI) is essential for achieving sustainable regional development and addressing the long-standing urban–rural dual-structure divide. This study investigates the impact of factor mobility—specifically labor, capital, and land—on URI across 1712 Chinese counties. By constructing a multidimensional evaluation system for URI and employing a Spatial Durbin Model (SDM), we unpack the direct and indirect effects, as well as the spatial spillover effects of these factors. The results indicate that URI levels in China exhibit significant positive spatial autocorrelation and distinct regional disparities. Labor and capital mobility significantly promote URI, manifesting robust positive direct effects and spatial spillovers that benefit neighboring counties. By contrast, land mobility reveals a “structural mismatch,” whereby inefficient land-use conversion can hinder integration, particularly in less-developed regions. Heterogeneity analysis further shows that the effects of factor mobility are strongest in Eastern China, while Western regions face structural constraints. These findings suggest that sustainable urban–rural transformation requires not only the free flow of production factors but also a coordinated spatial strategy to mitigate regional imbalances. This study provides policy-relevant insights for policymakers aiming to optimize factor allocation and enhance grassroots-level sustainability within the framework of rural revitalization and integrated regional development.

Grain production capacity is the first essential to ensure food security. Since the beginning of the 21st century, with the rapid urbanization process and significant climate change, China's grain production capacity has undergone a significant spatial reconstruction process. Based on the long-term multi-source provincial panel data from 2000 to 2022, this paper deconstructs the spatial reconstruction process of China's grain production capacity, identifies the dominant driving factors and key driving mechanisms, in order to provide scientific reference for China's food security and the United Nations Sustainable Development Goals. The results show that: (1) China's grain production capacity shows spatial and temporal significance and complexity in terms of production quantity, production potential and production structure. (2) The spatial center of gravity of the grain production quantity shifted from Southern Henan to Northern Henan and Southern Hebei. (3) The spatial autocorrelation and spatial stratification heterogeneity of the spatial distribution of production capacity are significant and increasing. The expansion and reduction of inter-provincial differences in production capacity coexist, and the primary distribution characteristics are not prominent and continue to weaken. (4) There are dimensional heterogeneity in the driving factors of production quantity, production potential and production structure. The two main controlling factors of climate change and urbanization are changing in the process of spatial reconstruction of grain production capacity. Climate change is dominant in the early stage and urbanization is dominant in the later stage. (5) Under the coupling of urbanization and climate change, the nonlinear spatial reconstruction process of grain production capacity occurs at three levels of production quantity, production structure and production potential. (6) Agricultural policies can directly inhibit excessive "non-grain" and "non-agricultural" transformation by ensuring agricultural land input and increasing agricultural economic benefits, thereby regulating production structure, ensuring production quantity and improving grain production capacity.

In China, the “land-restructuring” policy provides balanced land for urban settlements that is strictly limited in expansion. Therefore, reassessing and adjusting the layout of rural settlements is of great practical significance for promoting rural revitalization. In this paper, taking Xian’an district in Hubei Province as an example, we use the weighted rank-sum ratio comprehensive evaluation method and spatial association analysis method to analyze the development level and spatial pattern of settlements. The results show that: (1) The development level of settlements in Xian’an shows obvious spatial differences, with a spatial pattern of ‘high in the core–low in the periphery’ and ‘high in the northwest–low in the southeast’, which is the result of the combined effect of natural geographical conditions and socioeconomic conditions; (2) The comprehensive development level of settlements, evaluated based on four major indicators—population size, resource endowment, spatial characteristics, and material construction—reveals the presence of cluster effects, distance decay effects, administrative hierarchy effects, and “long board” effects; (3) Within village communities, settlements with significantly high levels and settlements with significantly low levels have a similar geographic distribution and mosaic spatial patterns. Lastly, based on the overall development level and spatial association patterns of settlements, this article presents possible options for governmental settlement governance from the standpoint of rural building management.

The global pursuit of sustainable urban development is often undermined by the classic rebound effect where gains in energy utilization efficiency are paradoxically offset by increased consumption. This challenge underscores the limitations of isolated technological fixes and calls for a more systemic framework. Under this background, China's national strategy of "New Quality Productive Forces" (NPRO) presents a novel paradigm, yet its causal impact on urban energy utilization efficiency (TE) remains empirically underexplored. This study addresses this critical gap using a panel of 280 Chinese cities from 2010–2022, employing Double Machine Learning (DML) for robust causal inference and spatial econometric models to quantify spillover effects. The findings are as follows: first, the spatial analysis uncovers a pattern of asynchronous evolution. NPRO generation exhibits strong geographic stickiness in eastern coastal hubs, whereas its TE benefits display a broad diffusion pattern inland, driven by positive spatial spillovers to economically interconnected neighboring regions. Second, causal evidence indicates that NPRO significantly enhances urban energy efficiency; a one-standard-deviation increase in the NPRO index is associated with a 0.644-standard-deviation improvement in TE. Third, positive effect is primarily channeled through two institutional mechanisms: the intensification of low-carbon policies and the enhancement of governance transparency. Finally, this positive impact is heterogeneous, proving most pronounced in cities that prioritize environmental protection, possess advanced industrial structures, are in the eastern region, or have a lower degree of government intervention. Ultimately, this study offers robust causal evidence that a systemic, state-led productivity framework can mitigate traditional efficiency paradoxes, providing crucial implications for designing spatially-aware energy transition policies in emerging economies.