The study of urban spatial structure is currently one of the most popular research fields in urban geography. This study uses Lanzhou, one of the major cities in Northwest China, as a case area. Using the industry classification of POI data, the nearest-neighbor index, kernel density estimation, and location entropy are adopted to analyze the spatial clustering-discrete distribution characteristics of the overall economic geographical elements of the city center, the spatial distribution characteristics of the various industry elements, and the overall spatial structure characteristics of the city. All of these can provide a scientific reference for the sustainable optimization of urban space. The urban economic geographical elements generally present the distribution trend of center agglomeration. In respect of spatial distribution, the economic geographical elements in the central urban area of Lanzhou have obvious characteristics of central agglomeration. Many industrial elements have large-scale agglomeration centers, which have formed specialized functional areas. There is a clear “central–peripheral” difference distribution in space, with an obvious circular structure. Generally, tertiary industry is distributed in the central area, and secondary industry is distributed in the peripheral areas. In general, a strip-shaped urban spatial structure with a strong main center, weak subcenter and multiple groups is present. Improving the complexity of urban functional space is an important goal of spatial structure optimization.

Driven by economic development, the dramatic increase in carbon emissions has led to global warming and a series of environmental problems. The question of how to ensure harmonized coordination between economic development, carbon emissions and environmental protection has become increasingly important. The conflicts between the use of energy and emission reductions in China have become more intense. It is an inevitable requirement for China’s sustainable development to promote a low-carbon circular economy and the simultaneous and coordinated development of carbon emissions, the economy and the environment. The present study took 30 provinces (municipalities and autonomous regions directly under the Central Government) as the research objects (Tibet, Hong Kong, Macau, and Taiwan are not included in the study due to the lack of relevant data), and applied quantitative analysis methods, such as three-stage data envelopment analysis (DEA) models, coupling coordination degree models and spatial analysis models, to construct a measurement index system. On the basis of the measurement of its carbon emission efficiency, the level of China’s coordination degree in regard to carbon emissions, economic development, and environmental protection at both spatial and temporal dimensions was analyzed comprehensively in order to reveal its temporal and spatial characteristics. The conclusions are as follows: (1) China’s overall carbon emission efficiency displayed a gradual upward trend, although the overall level was not that high. Therefore, there is still much scope for further improvement. (2) The level of China’s coordination degree in regard to carbon emissions, economic development, and environmental protection showed a steady yet rising trend. All provinces reached different levels of coordination development, and there was no province that displayed a disorderly declining trend. However, the number of provinces that reached or went beyond the intermediate level of coordination development was quite limited. (3) The level of China’s coordination degree in regard to carbon emissions, economic development, and environmental protection displayed obvious spatial aggregation patterns at the provincial level, showing an apparent spatial dependence and heterogeneity. Over time, the level of spatial aggregation patterns in regard to coordination degree tended to weaken. Overall, the values were high in the eastern region and low in the western region, decreasing from the eastern coastal zone towards the western inland zone, thus demonstrating a contrasting east-west spatial distribution pattern.

Watershed ecosystems are crucial to the overall sustainable development of a region, and a scientific and effective grasp of the characteristics of land-use change in a watershed, and the factors affecting land change, is an important prerequisite for the high-quality construction of watershed ecology, which needs to be emphasized. As the second largest inland river in the arid zone of Western China, the Heihe River Basin (HRB) has been affected by human and natural factors in recent years, and the ecological environment is relatively fragile, and there is an urgent need to analyze the ecological characteristics of the basin and to explore the relevant influencing factors in order to provide a basis for subsequent ecological management. Therefore, this article applies the landscape index, the landscape ecological risk index (ERI) model and the geodetector tools to analyze the land-use data from 2000 to 2020 in the Zhangye area of the HRB to study the characteristics of the ecological risk evolution and the driving forces affecting the ecological risk differentiation. The results show the following: (1) the area of the regional land-use change accounts for 4.99% of the total area, and the landscape pattern as a whole shows an increasing degree of fragmentation and a decreasing trend of aggregation; (2) the distribution of the ERI in the region shows a trend of being low in the center and high in the periphery, with an increase of 2.11% in the area of the lowest and lower risk and a decrease of 1.77% in the highest and higher, and the temporal change shows an increase followed by a significant decrease; (3) the human interference degree is the dominant factor influencing the spatial differentiation of the ERI in the basin area. There are significant differences between social factors, climate factors and land factors.

In the 21st century, problems relating to energy, economy, and the environment have become increasingly severe across the world, and critical issues around environmental pollution, ecological imbalance, and an energy crisis have emerged. The Yellow River basin is an important ecological barrier, economic region, and energy base in Northern China. Environmental pollution in the Yellow River basin has become increasingly problematic, especially since the reform and opening up of China, along with the rapid development of the industrial economy and mining for energy resources. In this study, 64 of the 73 prefecture-level cities in the Yellow River basin were selected as the research object, including 18 cities in the downstream region, 26 cities in the midstream region, and 20 cities in the upstream region. The data used in this study were from 2004 to 2019. On the basis of temporal variation and spatial differentiation of the three factors of economy, energy, and environment, the impulse response function and the generalized method of moments (GMM) were adopted to evaluate the effects of energy utilization and economic growth on the ecological environment. Their roles in affecting the ecological environment were analyzed along with the underlying mechanisms. Overall, energy utilization, economic growth, and ecological environment are in good condition, showing a steady upward trend. Regional differences still exist, but the gap is gradually narrowing. There are some differences in the impulse response of the ecological environment to the economic growth and energy utilization in the upstream, midstream, and downstream regions of the Yellow River basin. The effect is leveled out or weakened in the middle and later phases of the impact. Compared with the downstream and upstream regions, economic growth and energy utilization in the midstream regions have less impact on the ecological environment. The two factors of energy utilization potential and economic potential have significant positive impacts on the ecological environment. The current situation of energy utilization has to some extent a positive impact on the ecological environment. Economic scale has a certain negative impact on the ecological environment.

The rational allocation of land resources is crucial to ensuring human well-being, livelihood, and survival. The study of Production-Living-Ecological Space (PLES) provides new perspectives on land resource allocation. However, few studies have assessed the feasibility of PLES optimization in ecological transition zones. For this study, using the composite functional space classification method, a classification and functional utility scoring system were constructed. Various methods, including dynamic attitude, transfer matrix, and spatial autocorrelation, were employed to characterize the evolution of the quantity and quality of PLES in the Hexi Corridor. Moreover, the mechanisms driving these changes were explored using a geodetector. Our findings revealed that: (1) The distribution of Production-Ecological Space (PES) is higher in the west and south and lower in the east and north. Production-Living Space (PLS) is scattered. Ecological-Production Space (EPS) is mostly distributed in the south or west, whereas Ecological Space (ES) is mainly located in the north and west of the Hexi Corridor. (2) From 1980 to 2020, the area of PES and PLS increased by 2037.84 km² and 673 km², respectively; the area of EPS was relatively stable, and the area of ES decreased by 2523.06 km². (3) The evolution of PLES quality indicated that the high functional utility area of PES and PLS was roughly the same as the expanded functional utility area, whereas the expanded functional utility area of EPS and ES is similar to the median functional utility area. (4) The spatiotemporal evolution of PLES is closely linked to natural, economic, and social factors.

Since its emergence, the development of agriculture has always been closely related to changes in the natural environment. The productivity and development of agriculture largely depend on natural conditions and agriculture and has an important impact on the environment. The development of modern conventional agriculture has also led to a series of ecological, economic, and social problems that threaten human development and sustenance. China has historically been heavily reliant on agriculture and provides food and clothing for approximately 22% of the world’s population while only accounting for 9% of the world’s cultivated land and 6% of freshwater resources. Since the 21st century, the agricultural development of China has faced increasing resource and environmental constraints due to rapid industrialization and urbanization. Based on the perspective of efficiency evolution, data envelopment analysis (DEA) and spatial autocorrelation analysis (SAA) were used to test the environment adaptability efficiency within China’s agricultural systems across 30 provinces, autonomous regions, and municipalities, and explore its temporal and spatial evolution patterns and characteristics. Our study thus possesses both theoretical and practical significance. Furthermore, this study would enable the development of methods to assess China’s agricultural systems, in addition to providing a theoretical basis and guidelines for the creation of sustainable agriculture development strategies both in China and in other countries and regions. The following are the main conclusions of this study: (1) from 2000 to 2018, the overall environmental adaptability efficiency within China’s agricultural systems exhibited a gradual upward trend, achieving a transition from medium-level efficiency towards high-level efficiency, and the environmental adaptability of agricultural systems continued to increase. However, a certain gap remained between the level achieved and the DEA’s level of effectiveness, and therefore additional efforts are required to close this gap. (2) The environmental adaptability efficiency within China’s agricultural system showed a significant positive correlation in spatial distribution. Particularly, clear spatial aggregation characteristics were observed at the provincial level, which was also characterized by strong features of spatial dependence and spatial heterogeneity. Moreover, the degree of spatial aggregation increased gradually over time. High-value areas were mainly located along the southeast coastal area, whereas low-value areas were primarily located in the inland areas of the northwest. Therefore, environmental adaptability efficiency generally followed a northwest-southeast spatial distribution.