Taking China’s industrial land transfer data as the data source, this study quantitatively analyzes the transfer structure and spatial distribution of China’s industrial land from 2010 to 2019. By constructing the information entropy and the equilibrium degree model of industrial land-use structure, this study evaluates the transfer characteristics of industrial land of different functional types in various provinces of China, analyzes the scale advantages of various types of transferred industrial land by using the land transfer scale advantage index, and summarizes the spatial distribution characteristics of different types of industrial land transfer in China through the spatial center of gravity analysis and cold/hot spot regional distribution mapping. The following results were obtained. (1) There are significant differences in the transfer scale of industrial land among provinces in China. The transfer scale of Eastern and Central China is large, whereas that of Western China is small. (2) From the perspective of land-use structure, the transfer scale of industrial land in the central and western regions is more balanced than that in the east. (3) From the gravity center distribution of the standard deviation ellipse, the land transfer direction of the energy industry, and the mining industry, and other types of industries is more significant than that of the culture and sports hygiene industries, modern manufacturing industry, and high-tech industry. (4) From the analysis of cold and hot spots, the mining industry, the energy industry, and other types of industries in the western region with rich mineral resources are the hot spots of industrial land transfer, and the southeast coast is the cold spot; the eastern coastal area is a hot area for land transfer of modern manufacturing, the high-tech industry, and the culture and sports hygiene industries. The results reveal the regional differences and spatial distribution characteristics of industrial transfer in China and provide a reference for authorities to formulate industrial planning and industrial land collection, storage, and transfer plans.

As China’s economic development has entered a new phase, China needs to seek a new path of green transformation development to coordinate the economic growth with environmental mitigation. From 2002 to 2017, green investment in China grew from 118.56 billion Chinese yuan to 950.86 billion Chinese yuan, increasing more than seven times. In this study, a homothetic shift-share analysis (HSSA) is used to understand how green investment changed and was used to decompose the change of provincial green investment in China from 2002 to 2017 into four driving factors: the national economic growth effect (NEG), national green investment structure effect (NIS), homothetic regional green investment competition effect (HRIC), and regional green investment allocation effect (RIA). The results indicate that these four factors had various regional and temporal characteristics, although green investment increased in all provinces during this period. More specifically, the NEG was more significant in the east than in other regions. The regional differences of NEG were relatively large in the first two periods (2002–2007 and 2007–2012) and began to shrink in the third period (2012–2017). The NIS shared the same characteristics as the NEG. In terms of HRIC, the central region was ahead of the eastern and western regions, and relatively many eastern provinces were with negative HRIC. The HRIC of most provinces showed a trend of “low/medium-medium/high-low”. The RIA inhibited green investment growth in most provinces and showed a “high-low-high” trend regarding the change from 2002 to 2017. Our study suggests that it is necessary to coordinate the growth of green investment across different regions and establish an ecological compensation mechanism.

Solar photovoltaic (PV) has become the fastest-growing new energy in China and one of the main contributors to China’s clean energy transition. From 2013 to 2019, China’s solar PV installed capacity grew from 15,890 MW to 204,180 MW, increasing by 11.85 times. To explore solar PV investment changes across China regions, we use spatial shift-share analysis model to decompose solar PV investment changes from 2013 to 2019 into four components: national energy investment growth effect (NEG), national energy investment structure effect (NES), neighbor–nation solar PV investment competitive effect (NNC), and region–neighbor solar PV investment competitive effect (RNC). Based on the decomposition results, we find that the value of NNC of most western provinces is negative for the entire period, while the NNC of most central and eastern provinces is in the middle and lower range. There is little difference in RNC among these regions. While comparing the influence caused by the four effects, NNC and RNC play dominant roles in solar PV investment changes in eastern and central provinces, which means NEG and NES have relatively small impacts. By contrast, NEG and NES affect the solar PV investment changes at a larger scale in most western provinces. Comparing the NNC and RNC, we find that RNC played a prominent role in the eastern and central regions, while NNC played a dominant role in the west.