This study examines the spatial distribution of consumption competitiveness and carrying capacity across regions, exploring their interrelationship and implications for sustainable regional development. An evaluation index system is constructed for both consumption competitiveness and carrying capacity using a range of economic, social, and environmental indicators. We apply this framework to regional data in China and analyze the resultant spatial patterns. The findings reveal significant regional disparities: areas with strong consumption competitiveness are often concentrated in economically developed regions, while high carrying capacity is notable in less populated or resource-rich areas. Notably, a mismatch emerges in some regions—high consumer demand is not always supported by adequate carrying capacity, and vice versa. These disparities highlight potential sustainability challenges and opportunities. In the discussion, we address reasons behind the spatial mismatch and propose policy implications to better align consumer market growth with regional resource and environmental capacity. The paper concludes that integrating consumption-driven growth strategies with carrying capacity considerations is essential for balanced and sustainable regional development.

Assessment of water resources carrying capacity (WRCC) is of great significance for understanding the status of regional water resources, promoting the coordinated development of water resources with environmental, social and economic development, and promoting sustainable development. This study focuses on the Longdong Loess Plateau region and utilized panel data spanning from 2010 to 2020, established a three-dimensional evaluation index system encompassing water resources, economic, and ecological dimensions, uses the entropy-weighted TOPSIS model coupled with global spatial autocorrelation analysis (Global Moran’s I) and the hot spot analysis (Getis-Ord Gi* index) method to comprehensively evaluate the spatial distribution of the WRCC in the study region. It can provide scientific basis and theoretical support for decision-making on sustainable development strategies in the Longdong Loess Plateau region and other regions of the world.From 2010 to 2020, the overall WRCC of the Longdong Loess Plateau area show some fluctuations but maintained overall growth. The WRCC in each county and district predominantly fell within level III (normal) and level IV (good). The spatial distribution of the WRCC in each county and district is featured by clustering pattern, with neighboring counties displaying similar values, resulting in a spatial distribution pattern characterized by high carrying capacity in the south and low carrying capacity in the north. Based on these findings, our study puts forth several recommendations for enhancing the WRCC in the Longdong Loess Plateau area.

Although the problems created by exceeding Earth’s carrying capacity are real, a too-small population also creates problems. The convergence of a nation’s population into small areas (i.e., cities) via processes such as urbanization can accelerate the evolution of a more advanced economy by promoting new divisions of labor and the evolution of new industries. The degree to which population density contributes to this evolution remains unclear. To provide insights into whether an optimal “threshold” population exists, we quantified the relationships between population density and economic development using threshold regression model based on the panel data for 295 Chinese cities from 2007 to 2019. We found that when the population density of the whole city (urban and rural areas combined) exceeded 866 km⁻², the impact of industrial upgrading on the economy decreased; however, when the population density exceeded 15,131 km⁻² in the urban part of the cities, the impact of industrial upgrading increased. Moreover, it appears that different regions in China may have different population density thresholds. Our results provide important insights into urban economic evolution, while also supporting the development of more effective population policies.