Ling Jiang

Background: Conducting an extensive study on the spatial heterogeneity of the overall carbon budget and its influencing factors and the decoupling status of carbon emissions from economic development, by undertaking simulation projections under different carbon emission scenarios is crucial for China to achieve its targets to peak carbon emissions by 2030 and to achieve carbon neutrality by 2060. There are large disparities in carbon emissions from energy consumption, the extent of land used for carbon absorption, and the status of decoupling of emissions from economic development, among various regions of China. Results: Based on night light data and land use data, we investigated carbon budget through model estimation, decoupling analysis, and scenario simulation. The results show that the carbon deficit had a continuous upward trend from 2000 to 2018, and there was a significant positive spatial correlation. The overall status of decoupling first improved and then deteriorated. Altogether, energy consumption intensity, population density of built-up land, and built-up land area influenced the decoupling of carbon emissions from economic development. There are significant scenarios of carbon emissions from energy consumption for the study area during the forecast period, only in the low-carbon scenario will the study area reach the expected carbon emissions peak ahead of schedule in 2027; the peak carbon emissions will be 6479.27 million tons. Conclusions: China’s provincial-scale carbon emissions show a positive correlation with economic development within the study period. It is necessary to optimize the economic structure, transforming the economic development mode, and formulating policies to control the expansion of built-up land. Efforts must be made to improve technology and promote industrial restructuring, to effectively reduce energy consumption intensity.

Floating population is an important group in the emerging urbanization process. This group promotes long-term settlement, which is a significant driving force increasing the urbanization level of countries. This study analyzed the changes in population mobility between Chinese cities and the willingness of the floating population to settle down. The analyses were based on data obtained from the China Migrants Dynamic Survey (CMDS) in 2017, and the China Seventh Census 2020. Spatial econometric models were constructed for in-depth research. The result showed that: ① the floating population migrated mainly from the central region to the surrounding cities, and their long-term settlement intention presented a spatial pattern of "high in the east, low in the west, and local concentration." ②the long-term settlement intention significantly negatively affected the urban floating population. City economic level, public service capacity, and environmental quality significantly positively or negatively influence the number of the floating population. For promoting more floating population to become urban residents, management of the group should be strengthened, construction level of the urban economy, society, and ecology improved, and the willingness of the group to settle for an extended time encouraged.

The future development of the world is threatened due to global warming and climate change mainly driven by carbon emissions. Conducting an extensive study on the influencing factors of regional energy consumption and prediction through scenario simulation is of great significance for China in order to meet its aim of achieving carbon peak by 2030. The affected areas of the lower Yellow River are one of the main grain-producing areas in China, and it is facing a strong demand for urbanization and rapid economic development. Based on the night light data, this study demonstrates that the carbon emissions from energy consumption in the study area showed an upward trend from 2000 to 2018 with obvious spatial distribution differences. Economic development had a significant positive effect on the increase in carbon emissions from energy consumption; energy consumption intensity showed a significant negative effect. The study area achieves the carbon peak target in 2027 only under the low-carbon scenario. This study is helpful to realize ecological protection and high-quality development in the Yellow River Basin and also has reference significance for other developing countries.

Achieving “Responsible Consumption and Production” is one of the 17 sustainable development goals set by the United Nations. Controlling overcapacity is an important guarantee in order to achieve this goal. There are many types and large quantities of raw materials in the construction industry, which easily leads to overcapacity. Studying the problems related to overcapacity in the construction industry helps to understand the formation mechanism of overcapacity in related industries. This puts forward targeted countermeasures and suggestions for the capacity resolution to achieve green and sustainable development. Based on this, this paper uses the construction industry capacity utilization data of the Shandong Province in China from 2005 to 2017. It also uses the production function method to construct a construction industry overcapacity calculation model to estimate the construction industry capacity utilization and overcapacity rate in Shandong Province. The DEA method was used to construct an extraction model of influencing factors for overcapacity. The results show that the capacity utilization ratio for Shandong Province from 2005 to 2016 was 81.98%. There was no overcapacity as a whole, but there were large fluctuations in capacity utilization for some time periods. Suggestions for optimization countermeasures were also proposed.