Exploring the factors that drive the change of ecosystem services (ES) is very important for maintaining ES function and zoning ecological management, especially in the Sichuan Basin area with high spatial heterogeneity such as natural and socio-economic characteristics. Taking the Sichuan Basin in China as an example, the PCA-MGWR model was constructed to explore the temporal and spatial patterns of ES in the Sichuan Basin from 2000 to 2015. The potential driving factors including anthropogenic factors, geomorphological factors, climate factors, and vegetation factors would be analyzed by principal component analysis (PCA). To illustrate the impact of spatial dependence in the data, the multi-scale geographically weighted regression (MGWR) technology was selected to explore the spatial differentiation of the impact of these four dimensions on ES to reflect the local differences of ecosystem service driving mechanisms in more detail. The results showed that 1) from the perspective of time series evolution, carbon storage (CS) and soil conservation (SC) in ES in the Sichuan Basin showed an upward trend, while water yield (WY) showed a downward trend; from the perspective of spatial patterns, except the main urban areas of Chengdu and Chongqing, the CS service level of other regions was high; The spatial distribution characteristics of SC services were “low in the middle and high in the periphery”; the high value area of WY service was located in Northeast Sichuan. 2) Among natural factors, elevation (DEM), slope (SLO), NDVI, annual average temperature (TEM), and annual average precipitation (PRE) had a higher contribution rate to ES, while among socio-economic factors, GDP density (GDP), night light (LIG), and population density (POP) had a higher contribution rate to ES, while other factors had a lower contribution rate. 3) Combined with the PCA-MGWR model, we analyzed the comprehensive response and spatial differentiation of driving factors to ES in the Sichuan Basin and explained in detail the influence of anthropogenic factors, geomorphological factors, climatic factors, and vegetation factors and their spatial heterogeneity in ES. It is expected that the spatial differences in the impact degree of different indicators can be considered when formulating the countermeasures of ES in the Sichuan Basin, to provide theoretical support for the implementation of regional ecological management and control.

The Yangtze River Delta region contributes nearly 16% of the national carbon emissions and is the key area for carbon emission reduction in China. Accurately grasping the spatial evolution characteristics of carbon emissions and the interaction between counties and regions is of great practical significance for precise and collaborative carbon reduction. This study firstly explores the spatial layout and dynamic evolution characteristics of county carbon emissions in the Yangtze River Delta region from 2000 to 2018 by using spatial statistical analysis, secondly identifies the influencing factors of county carbon emissions (CAR) in the Yangtze River Delta region from dynamic and static dimensions respectively by using static and dynamic Spatial Dubin Model, and finally judges the spatial spillover effects of each factor. We find that county carbon emissions are more complex and more diverse in non-synchronous state compared to provinces and cities. The high carbon areas in the Yangtze River Delta region are concentrated in Shanghai and its neighboring cities, as well as industrial counties under the jurisdiction of other sub-core cities, which are continuously clustered towards the center. We have made some theoretical discussions on the results of the spillover effects of various factors on carbon emissions, and concluded that economic of scale (ECO) and industrial structure (IND) have a “polarization effect”, population size (POP) is consistent with the Malthusian view, technological advance (TEC) has a “cumulative effect”, and environmental quality (ENV) The “pollution paradise effect” is mitigated. Finally, we believe that the main unit of precise carbon reduction can take the form of “city-county” combination, and the government should implement differentiated and coordinated carbon reduction policies.

Strategic emerging industries (SEIs) are an important industrial policy to promote innovation, develop advanced manufacturing, and upgrade the economy in China. The research explores the impact of SEIs on urban economic growth in mainland China, from agglomeration externalities and network externalities. The results show that SEIs have a significant impact on growth, and network externalities are generally more important than agglomeration externalities. Although the agglomeration of large‐scale listed enterprises in the city promotes growth, too many large enterprises in the cluster, that is, the lack of small and medium‐sized supporting enterprises, will harm urban growth. Meanwhile, a city with a higher degree of centrality has a larger GDP, but the strength has a negative impact.

We studied the misalignment between tourism resources and economic development in mountainous cities in the context of limited highway network accessibility. Using Lhasa City as a case study, we illustrated how to evaluate tourism resources and economic development and how to improve tourism resources and promote economic development. The tourism resources possessed by tourism destinations are prerequisites for tourism activities. This study focuses on the coupling coordination relationship between the degree of superiority in tourism resources and the level of economic development in Lhasa City. Data from Lhasa City in 2010, 2015, and 2020 were compared to explore a way of optimizing the spatial pattern of tourism development. The results of this study are as follows. (1) As a typical mountainous area on the Qinghai–Tibet Plateau, the accessibility of Lhasa’s mountainous area largely influences the choice of tourist destinations and is also an important indicator for evaluating the degree of tourism resource superiority. (2) On the whole, the economic development of Lhasa City and the degree of tourism resource superiority is not coordinated, mainly in the low coupling coordination stage, and with the passage of time, the degree of coupling coordination gradually becomes weaker. (3) If a town has advantageous tourism resources with slow economic development, it is easy to fall into the “resource curse” dilemma. In addition, if a town has poor tourism resources, it will be reduced to an outflow area of population and resources after leaving the investment drive, and easy to fall into the dilemma of the “poverty trap”.

Resource-based cities (RBCs) face persistent challenges from the “resource curse,” making industrial transition imperative for sustainable development. While the necessity of this transition is clear, the optimal pathways for implementation remain debated. This study investigates how external factor flows drive national value chain (NVC) upgrading in RBCs across different development stages. This study uses a city-level multiregional input-output table and a dynamic panel model to analyse how technology, capital, and labor flows affect the NVC positions of resource- and nonresource-based sectors across 80 Chinese RBCs. Our findings reveal that external technology and capital inflows enhance overall NVC positions, with capital specifically boosting resource-based sectors and both factors elevating nonresource-based sectors. The effectiveness of these factors varies significantly across urban development periods: during the growth period, capital and skilled labor drive respective upgrades in resource- and nonresource-based sectors. During the maturity period, technology inhibits the upgrading, with capital only restraining the upgrading of nonresource-based sectors and skilled labor upgrading nonresource-based sectors. During the depletion period, only capital drives the upgrading of resource-based sectors. In the regeneration period, technology drives the upgrading of both resource- and nonresource-based sectors, whereas capital and skilled labor drive the upgrading of nonresource- and resource-based sectors, respectively. These findings offer strategic guidance for RBC policymakers to align external engagement strategies with specific development stages, advancing sustainable development goals.