The demand structure of resources for new economy is different from the traditional one in that its development may significantly change China’s economic location map and spatial pattern. Based on 343 administrative units of prefecture-level cities in China, this research constructs the measurement index system of terrestrial surface natural resources under the orientation of the new economic demands; this research mainly analyses the spatial distribution characteristics and geographical mechanism of natural resources by means of the spatial autocorrelation and spatial similarity calculation methods. The results show that: (1) The structure and endowment of natural resources under the orientation of the new economic demands need to be reexamined. The significance of a good environment and ecological resources has been highlighted. The coupling of resource elements better reveals the availability of natural resources. (2) The natural resources decrease from southeast to northwest, showing a pattern of “abundant in the south and east and scarce in the north and west”. Natural resources have a significant positive correlation in spatial distribution with two types of agglomeration: high-high agglomeration and low-low agglomeration, showing the local agglomeration feature of “high in the south and low in the north”. (3) Natural factors such as temperature, precipitation and altitude affect the spatial distribution of natural resources, with the temperature being the most significant. This indicates that the original natural environment and its role are the geographical mechanism for the formation and distribution of natural resources. The results could provide a reference for the development and the optimization of China’s new economy.

To investigate the spatiotemporal patterns of fine particulate matter (PM_2.5) under years of control measures in China, a comprehensive analysis including statistical analysis, geographical analysis, and health impact assessment was conducted on millions of hourly PM_2.5 concentrations data during the period of 2017–2020 in six typical major urban agglomerations. During the period of 2017–2020, PM_2.5 concentrations in the Beijing–Tianjin–Hebei urban agglomeration (BTH-UA), Central Plains urban agglomeration (CP-UA), Yangtze River Delta urban agglomeration (YRD-UA), Triangle of Central China urban agglomeration (TC-UA), Chengdu–Chongqing urban agglomeration (CY-UA), and Pearl River Delta urban agglomeration (PRD-UA) decreased at a rate of 6.69, 5.57, 5.45, 3.85, 4.66, and 4.1 µg/m³/year, respectively. PM_2.5 concentration in BTH-UA decreased by 30.5% over four years, with an annual average of 44.6 µg/m³ in 2020. CP-UA showed the lowest reduction ratio (22.1%) among the six regions, making it the most polluted urban agglomeration. In southern BTH-UA, northeastern CP-UA, and northwestern TC-UA, PM_2.5 concentrations with high levels formed a high–high agglomeration, indicating pollution caused by source emission in these areas was high and hard to control. Atmospheric temperature, pressure, and wind speed have important influences on PM_2.5 concentrations. RH has a positive correlation with PM_2.5 concentration in north China but a negative correlation in south China. We estimated that meteorological conditions can explain 16.7–63.9% of the PM_2.5 changes in 129 cities, with an average of 33.4%, indicating other factors including anthropogenic emissions dominated the PM_2.5 changes. Among the six urban agglomerations, PM_2.5 concentrations in the CP-UA were most influenced by the meteorological change. Benefiting from the reduction in PM_2.5 concentration, the total respiratory premature mortalities in six regions decreased by 73.1%, from 2017 to 2020. The CP-UA had the highest respiratory premature mortality in six urban agglomerations. We suggested that the CP-UA needs more attention and stricter pollution control measures.

The formation and development of cities are inseparable from a certain scale of water resources. The information contained in the morphological structures of cities and water systems is often overlooked. Exploring the spatiotemporal evolution of water system structures (WSS) and urban system structures (USS) can reveal the “urban–water” relationship from a new perspective. The Huaihe River Basin (HRB) was selected as the case area, based on the theory of fractal dimensions, grid dimension and multifractal spectrum methods were used to depict the structural evolutionary characteristics of water systems and urban systems from different dimensions. Then, through a comparative analysis of fractal parameters and spectral lines, the characteristics and changing patterns of the “urban-water” relationship in the HRB from 1980 to 2019 were revealed. The results indicate the following: (1) The water system structure in the HRB is complex and exhibits distinct scale characteristics, showing improvement overall and at larger scales while continuously degrading at smaller scales. (2) Both the water system and urban system exhibit increasingly complex spatial development characteristics; however, the USS continues to optimize over time, while the WSS experiences degradation. (3) The development patterns of the water system and urban system are significant differences in the HRB. Urban development mainly relies on outward expansion, whereas the water system is primarily characterized by intensive enhancement. (4) Because of the rapid development of urban areas, water scarcity may occur in densely populated urban areas or larger cities in the future. The research results can serve as a scientific reference for urban planning and water resource management in the HRB.