As a regional management unit to solve "urban diseases,” metropolitan areas are gradually attracting widespread attention. How to objectively and accurately delineate the boundaries of a metropolitan area is the primary prerequisite for carrying out targeted studies and precisely formulating regional planning measures. However, the existing methods for delineating metropolitan area boundaries have problems, such as high data acquisition costs, subjectivity, and a single perspective of urban linkage. To address the above problems, we propose a “bottom-up” approach to metropolitan area boundary delineation based on urban comprehensive spatial linkages. We used only publicly available data to construct a directionally weighted network of urban spatial linkages, and applied community detection algorithms to delineate metropolitan area boundaries. Taking the Beijing–Tianjin–Hebei region as a case study area, the method’s validity was confirmed. The results showed the following: (1) Eight metropolitan areas were delineated within the region, with two types of metropolitan areas: “Inter-municipal” and “single-city”. (2) The overall accuracy of the delineation results reached 83.41%, which is highly consistent with their corresponding isochrone maps. (3) Most metropolitan areas were observed to have an obvious “central–peripheral” structure, with only the JingJinLang metropolitan area being a polycentric mature metropolitan area, whereas the other metropolitan areas remained in the initial stage of development, with Zhangjiakou and Chengde not yet having formed metropolitan areas. This study’s methodology highlights the basic criteria of “inter-city spatial linkage” as the foundation for boundary delineation, avoiding the inaccuracy caused by the subjective selection of boundary thresholds, and can also accurately determine the developmental stage and internal spatial structure of metropolitan areas. Our method can provide new perspectives for regional boundary delineation and spatial planning policy formulation.

China’s growing electricity consumption has become an important factor to improving socio-economic development, as well as aggravating environmental degradation. Based on the provincial level data in China for the entire period and every five years during 2000–2015, this paper used a spatial shift-share analysis (SSS) to detect the driving factors of electricity consumption changes in China, mainly focusing on the spatial spillover effects of electricity consumption which have been ignored by previous literature. Results show that economic growth and industry structure change have increased China’s electricity consumption by 8919 and 746 billion kWh, respectively, while the electricity efficiency improvement has reduced China’s electricity consumption by 5337 billion kWh for the entire period. Among the total decrease in China’s electricity consumption caused by electricity efficiency improvement, about 20% is caused by spatial spillover effects, which cannot be ignored. Moreover, there are great differences in electricity consumption changes’ components across China’s provinces. The results provide a quantitative and better understanding of the determinants of China’s electricity consumption changes, and practical implications for differentiated electricity consumption regulation policies and regional energy cooperation strategies for China, as well as for other similar countries.

The coordinated development of Beijing–Tianjin–Hebei (BTH) is a major regional strategy in China that aims to alleviate Beijing’s non-capital functions and address the “big city disease”. Understanding the spatial distribution and changing trends of industrial development in BTH is critical for achieving BTH’s coordinated development goals. In particular, it is important to assess the effectiveness of Beijing’s non-capital functions at the industrial level. This study utilized the 2013 and 2018 economic census data and statistical methods such as spatial Gini coefficient, trend analysis, specialization index, and industry similarity. We first characterized the industrial development pattern by analyzing the spatiotemporal changes of the operating income and the number of legal entities in BTH urban agglomeration. Then, we identified the changes in the leading industries and industrial structure of different cities in BTH urban agglomeration from 2013 to 2018. The results indicate that the coordinated development policy has influenced the industrial structure of the BTH urban agglomeration, with an 85.53% increase in the number of legal entities and a 14.61% increase in operating income. Beijing’s non-capital functions have achieved initial results, mainly involving technology-intensive and knowledge-intensive tertiary industries such as information technology, finance, and scientific research. The division of industry and the development positioning of the three regions are gradually becoming clear. Our results show how the economic census data and spatial analysis can support significant advances in evaluating industrial and economic development patterns, and they can be used worldwide in the future.

Sustainable metropolitan development depends on the effective transformation of spatial linkages into functional integration, including efficient commuting, equitable public service accessibility, spatial connectivity, and cross-boundary governance. However, existing studies often rely on administrative boundaries, static indicators, or coarse spatial units, limiting their ability to identify fine-scale spatial heterogeneity and explain how metropolitan linkages shape functional integration. Taking the Beijing Metropolitan Area as a case study, this study develops an integrated framework combining metropolitan boundary delineation, spatial linkage network analysis, and spatial–functional urban integration assessment. SDGSAT-1 nighttime light data (NTL) and transport accessibility analysis are used to identify Beijing’s main urban center and delineate the metropolitan extent. Population flow, resource linkage, and comprehensive spatial linkage networks are constructed to characterize network structure and nodal hierarchy. Spatial–functional urban integration is then evaluated at the township/subdistrict scale from three dimensions: commuting integration, public service accessibility, and spatial connectivity. The results show that Beijing’s main urban center extends beyond the traditional central urban area, and the metropolitan area exhibits concentric attenuation, directional differentiation, and heterogeneous expansion. Although cross-boundary linkages have emerged, the network remains dominated by Beijing’s core functions, with localized support from Tianjin and absorptive roles of adjacent Hebei areas. Spatial–functional integration advances primarily along major linkage corridors and key nodes, forming a hierarchical pattern consistent with the comprehensive spatial linkage network. These findings provide fine-scale spatial evidence for optimizing functional corridors, strengthening secondary nodes, improving public service allocation, and promoting cross-boundary spatial governance in sustainable metropolitan development.