The overexploitation of groundwater in China has raised concern, as it has caused a series of environmental and ecological problems. However, far too little attention has been paid to the relationship between groundwater use and the spatial distribution of water users, especially that of manufacturing factories. In this study, a factory scatter index (FSI) was constructed to represent the spatial dispersion degree of manufacturing factories in China. It was found that counties and border areas between neighboring provinces registered the highest FSI increases. Further non-spatial and spatial regression models using 205 provincial-level secondary river basins in China from 2016 showed that the scattered distribution of manufacturing plants played a key role in groundwater withdrawal in China, especially in areas with a fragile ecological environment. The scattered distribution of manufacturing plants raises the cost of tap water transmission, makes monitoring and supervision more difficult, and increases the possibility of surface water pollution, thereby intensifying groundwater withdrawal. A reasonable spatial adjustment of manufacturing industry through planning and management can reduce groundwater withdrawal and realize the protection of groundwater. Our study may provide a basis for water-demand management through spatial adjustment in areas with high water scarcity and a fragile ecological environment.

The mixture of agricultural and non-agricultural land-use represents a new pattern of urbanization in the Global South. This mixture has hindered the improvement of land-use productivity and makes it difficult to achieve the centralized disposal of pollutants, which has resulted in the waste of land resources and serious environmental problems. Although many studies have investigated land-use mixture, most of them remain descriptive and lack quantitative examination and an in-depth mechanism analysis. Using raster land-use data, this paper examines the spatiotemporal pattern of the land-use mixture in China between 1990 and 2015 by calculating join counts values supplemented by landscape metrics, and attempts to explain the regional variations in land-use mixtures in recent years. The results show that, between 2000 and 2010, land-use was more mixed in fast-growing regions such as Zhejiang, Fujian, Chongqing, Guangdong, and some major metropolises and mining cities, and that, between 2010 and 2015, land-use was more mixed in Central China. Additionally, the results of econometric models reveal that mixed land-use can be alleviated in regions with strict land planning and management, such as urban agglomerations in the Yangtze River Delta and the Pearl River Delta, as well as in areas with high levels of urbanization. Furthermore, the results of a spatial heterogeneity analysis show that strict land management has played an important role in reducing the land-use mixture in Eastern China; however, it has not played a significant role in Central China. The findings of this study suggest that land-use should be appropriately planned and managed to ensure sustainable development.

Understanding the reasons for the differences in the spread of COVID-19 in different cities of China is important for future epidemic prevention and control. This study analyzed this issue from the perspective of population migration from Wuhan (the epicenter of the COVID-19 outbreak in China). It reveals that population outflow from Wuhan to other cities in Hubei Province (the province where Wuhan is located) and metropolises and provincial capitals outside of Hubei province exceeded those to other cities. This is broadly consistent with the distribution of confirmed COVID-19 cases. Additionally, model analysis revealed that population outflow from Wuhan was the key factor that determined the COVID-19 situations. The spread of COVID-19 was positively correlated with GDP per capita and resident population and negatively correlated with the distance from Wuhan and the number of hospital beds, while population density was not a strong influential factor. Additionally, the demographic characteristics of population migration from Wuhan also affected the virus transmission. Particularly, businesspeople (who tend to have a high frequency of social activities) were more likely to spread COVID-19. This study indicated that specific measures to control population outflow from the epicenter at the early stage of the epidemic were of great significance.