Eco-efficiency is a tool for sustainability analysis that indicates how to carry out economic activities effectively. This paper assesses agricultural eco-efficiency using data envelopment analysis (DEA) and the Theil index approach. Using basic data of 31 provinces in China during 2003–2013, we analyzed the agricultural eco-efficiency development level and spatial pattern in China. The results show that the agricultural eco-efficiency of only four provinces has been relatively efficient in the entire study period, namely, Zhejiang, Hainan, Chongqing, and Tibet. The results also show that agricultural eco-efficiency was higher mainly in south of the Qinling Mountains-Huaihe River Line and north of the Yangtze River area, that agricultural eco-efficiency is mainly affected by pure technical efficiency, and that highly efficient areas are mainly concentrated in the densely populated areas, i.e., the economic developed areas (except Tibet). The Theil index results show that the agricultural eco-efficiency difference weakened between provinces in China, as did western and northeast regions, but eastern and central regions show a slight upward trend.

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.

The study of the carbon emission intensity of agricultural production is of great significance for the formulation of a rational agricultural carbon reduction policy. This paper examines the regional differences, spatial–temporal pattern and dynamic evolution of the carbon emission intensity of agriculture production from 1991 to 2018 through the Theil index and spatial data analysis. The results are shown as follows: The overall differences in carbon emission intensity of agriculture production presents a slightly enlarging trend, while the inter-regional differences in carbon emissions intensity is decreasing, but the intra-regional difference of carbon emissions intensity presented an expanding trend. The difference in carbon emission intensity between the eastern and central regions is not obvious, and the difference in carbon emission intensity in the western region shows a fluctuating and increasing trend. The overall differences caused by intra-regional differences; the average annual contribution of intra-regional differences is 67.84%, of which the average annual contribution of western region differences is 64.24%. The carbon emission intensity of agricultural production in China shows a downward trend, with provinces with high carbon emission intensity remaining stable, while provinces with low intensity are expanding. The Global Moran’s I index indicates that China’s carbon emission intensity of agricultural production shows a clear trend of spatial aggregation. The agglomeration trend of high agricultural carbon emission remains stable, and the overall pattern of agricultural carbon emission intensity shows a pattern of increasing differentiation from east to west.

Tourism efficiency is an effective index of measuring the development quality of the tourism industry. In this study, the tourism efficiency of 30 provinces in China during the period from 2006 to 2018 was measured with the SBM model and Malmquist index. On the basis of ESDA and GWR models, we explored the spatial pattern of China’s tourism efficiency and the spatial heterogeneity of the influencing factors in depth. The results revealed that China’s tourism efficiency has been constantly enhanced with an increasingly balanced pattern. Meanwhile, the utilization degrees of various input factors have constantly been improving. Both technological efficiency and technological progress jointly promote rapid growth of total-factor productivity. Accompanied with constant enhancement of the spatial agglomeration effect, the local spatial pattern also showed obvious differentiation. In general, low-efficiency regions were mainly concentrated in northern China, while high-efficiency regions were concentrated in southern China. The distinct spatial–temporal differentiation characteristics of tourist economic efficiency can be attributed to different influencing strengths of various factors in various regions and different action tendencies. The level of economic development, traffic conditions, the professional level of tourism, and openness degree can significantly promote tourism efficiency. Tourism resource endowment and environmental cost impose slight effects and differ in action direction, thereby inhibiting the tourism efficiency of many regions.

As the largest solid waste (SW) generator in the world, China is facing serious pollution issues induced by increasing quantities of SW. The sustainability assessment of SW management is very important for designing relevant policy for further improving the overall efficiency of solid waste management (SWM). By focusing on industrial solid waste (ISW) and municipal solid waste (MSW), the paper investigated the sustainability performance of SWM by applying decoupling analysis, and further identified the main drivers of SW change in China by adopting Logarithmic Mean Divisia Index (LMDI) model. The results indicate that China has made a great achievement in SWM which was specifically expressed as the increase of ISW utilized amount and harmless disposal ratio of MSW, decrease of industrial solid waste discharged (ISWD), and absolute decoupling of ISWD from economic growth as well. However, China has a long way to go to achieve the goal of sustainable management of SW. The weak decoupling, even expansive negative decoupling of ISW generation and MSW disposal suggests that China needs timely technology innovation and rational institutional arrangement to reduce SW intensity from the source and promote classification and recycling. The factors of investment efficiency and technology are the main determinants of the decrease in SW, inversely, economic growth has increased SW discharge. The effects of investment intensity showed a volatile trend over time but eventually decreased SW discharged. Moreover, the factors of population and industrial structure slightly increased SW.

The issue of how to realize the coordinated development of various elements in human–land systems, or, in other words, how to achieve the coordinated development of population-economy-society-resource-environment (PESRE) systems, has become an important topic, which has received global attention. This study takes 31 provinces in China as the research objects, and carries out the research on the spatial–temporal synthetic measurement of the coordinated development of PESRE systems. The conclusions are as follows. From 1995 to 2015, the process of change of coupling coordination degree of China’s PESRE systems can be divided into two types: Rising first and then declining, and fluctuant continuously. The number of provinces of the first type was higher, and most provinces were on the verge of uncoordinated development status or in a weakly coordinated development status. The coupling degree of PESRE systems at the provincial level in China generally shows some positive spatial correlations, and the level of coordinated development displays some obvious spatial aggregation patterns. Moreover, the degree of such aggregation first increases and then weakens. The eastern parts of China represent the main “high-high” type aggregation regions. The central and western parts of China represent the main “low-low” types, account for the largest proportion, and display obvious aggregation characteristics.