Food self-sufficiency in a large country with 1.4 billion people is very important for the Chinese government, especially in the context of COVID-19 and the Russian–Ukrainian conflict. The objective of this paper is to explore the spatial–temporal evolution and driving factors of non-grain production in thirteen major grain-producing provinces in China, which account for more than 75% of China’s grain production, using 2011–2020 prefecture-level statistics. In the present study, the research methodology included GIS spatial analysis, hot spot analysis, and spatial Durbin model (SDM). The findings of this study are as follows: (1) The regions with a higher level of non-grain production were mainly concentrated in the central and western regions of Inner Mongolia, the middle and lower reaches of Yangtze River and Sichuan, while the regions with a low level of non-grain production were mainly distributed in the Northeast Plain. The regions with a higher proportion of grain production to the national total grain production were concentrated in the Northeast Plain, the North China Plain, and the Middle and Lower Yangtze River Plain of China. The hot spot regions with changes in non-grain production levels were mainly distributed in the Sichuan region and Alashan League City in Inner Mongolia, and the cold spot regions were mainly distributed in Hebei, Shandong, Henan, and other regions. (2) An analysis of the SDM indicated that the average air temperature among the natural environment factors, the ratio of the sum of gross secondary and tertiary industries to GDP, the ratio of gross primary industry to the GDP of economic development level, the urbanization rate of social development, and the difference in disposable income per capita between urban and rural residents of the urban–rural gap showed positive spatial spillover effects. The grain yield per unit of grain crop sown area of grain production resource endowment, the total population of social development, and the area sown to grain crops per capita of grain production resource endowment all showed negative spatial spillover effects. The research results of this paper can provide a reference for the country to carry out the governance of non-grain production and provide a reference for China’s food security guarantee.
With the rapid urbanization and industrialization of the past few decades, environmental issues have become increasingly prominent, and air pollution in the form of PM2.5 has become a major concern in China. The Chinese government has recognized the severity of these environmental challenges and has placed great emphasis on protecting the environment while promoting economic growth. This study utilizes remote sensing technology to analyze the spatio-temporal evolution characteristics of the decoupling between land-use intensity and PM2.5 in the Yangtze River Economic Belt (YREB) using 2000–2021 series of PM2.5 and land-use-change data, with the Mean Center Change analysis and the Tapio Decoupling Model. This study attempts to analyze the causes of change from the perspectives of economic development stage and policy execution. The study found that the average PM2.5 level decreased by 11.77 μg/m3 during this period, with high levels concentrated in urban areas and low levels found in less developed regions. The central trajectory of the land-use intensity shifted southeast, indicating a consistent trend in urbanization and industrialization in that direction. Meanwhile, the average land-use intensity value increased by 0.19, with the highest values concentrated in urban areas. A total of 71.12% of the regions in the YREB exhibited strong negative decoupling or negative decoupling between land-use intensity and PM2.5 levels, suggesting rapid urbanization and industrialization with a decrease in PM2.5 levels. These findings provide insight into the dynamic relationship between economic development, urbanization, and PM2.5 in China’s Yangtze River Economic Belt.
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