With economic globalization, the supply-and-demand gap of China’s minerals is becoming increasingly sharp, and the degree of dependence on imports is climbing, which poses a severe threat to the resource security for the country. From the perspectives of system and sustainable development, this paper develops a conceptual framework of mineral security, which is composed of five dimensions: availability, accessibility, technology and efficiency, sociability and governance, and environmental sustainability. Based on this framework, it constructs the evaluating metrics for measuring mineral security. Moreover, it employs the hybrid multiple criteria decision-making methods of Fuzzy analytic hierarchy process (AHP) and preference ranking organization method for enrichment evaluation (PROMETHEE) to assess the security performance for China’s several critical minerals, namely iron, copper, aluminum, lead, zinc, and nickel, with respect to the period of 2001 to 2015. The result indicates that the critical minerals of China were at a low to moderate level of security. Iron, copper, and nickel were in an unsecure situation for their short supply in China, and showed a downswing trend. On the other hand, as the preponderant minerals, lead and zinc were at a relatively secure position and uprising; however, they were exhausting their superiority for the huge and rapid-growth economic demand. Aluminum, as a mineral that China seriously depends on for imports, also demonstrated an upward trend due to the successful management of diversity of importing sources.

China’s rapid urbanization and industrialization have affected the spatiotemporal patterns of nitrogen dioxide (NO₂) pollution, which has led to greater environmental pressures. In order to mitigate the environmental pressures caused by NO₂ pollution, it is of vital importance to investigate the influencing factors. We first obtained data for NO₂ pollution at the city level using satellite observation techniques and analyzed its spatial distribution. Next, we introduced a theoretical framework, an extended stochastic impacts by regression on population, affluence, and technology (STIRPAT) model, to quantify the relationship between NO₂ pollution and its contributing natural and socio-economic factors. The results are as follows. Cities with high NO₂ pollution are mainly concentrated in the North China Plain. On the contrary, southwestern cities are characterized by low NO₂ pollution. In addition, we find that population, per capita gross domestic product, the share of the secondary industry, ambient air pressures, total nighttime light data, and urban road area have a positive impact on NO₂ pollution. In contrast, increases in the normalized difference vegetation index (NDVI), relative humidity, temperature, and wind speed may reduce NO₂ pollution. These empirical results should help the government to effectively and efficiently implement further emission reductions and energy saving policies in Chinese cities in a bid to mitigate the environmental pressures.