"Green" economic development in China: quantile regression evidence from the Yangtze River Economic Belt

Future carbon storages of ecosystem based on land use change and carbon sequestration practices in a large economic belt

Assessments of ecosystem carbon storage are needed to form the scientific basis for carbon policies. Due to lack of data, there are few accurate, large-scale, and long-term predictions of ecosystem carbon storage. This study used the Distributed Land-Use Change Prediction (DLUCP) model with ten socioeconomic and two climate change scenarios for a total of 20 combinations that take into account population increase, technology innovation, climate change, and Grain for Green Project to make high-resolution predictions of land use change in the Yangtze River Economic Belt. Low and high carbon sequestration practices were considered to predict future carbon densities. Land use change data, carbon densities data, and the InVEST model were used to predict changes in ecosystem carbon storage from now to 2070. The results show a slight increase (1.88-4.17%) in carbon storage in the study area only based on land use change. Grain for Green Project has the largest impact on carbon storage among population increase, technology innovation, climate scenarios, and Grain for Green Project, which increases carbon storage by 4.17%. After the implementation of carbon sequestration practices, there is an increase in carbon storages from 28.51 to 56.77% in the study area from now to 2070, and increasing carbon storages of forest in each stream and carbon storage of cropland in downstream are efficient ways to achieve carbon neutralization.

What were the spatiotemporal evolution characteristics and the influencing factors of urban land green use efficiency? A case study of the Yangtze River Economic Belt

China's rapid urbanization has had a tremendous impact on the country's limited land resources, and one of the major issues of green development is how to utilize the limited land resources to maximize social, economic, and environmental advantages. From 2005 to 2019, the super epsilon-based measure model (EBM) was employed to assess the green land use efficiency of 108 prefecture-level and above cities in the Yangtze River Economic Belt (YREB), as well as investigate its spatial and temporal evolution and influential factors. The findings demonstrate that overall, urban land green use efficiency (ULGUE) in the YREB has been ineffective; in terms of city scale, megacities have the highest efficiency, followed by large cities and small and medium-sized cities; and at the regional level, downstream efficiency does have the greatest average value, followed by upstream efficiency and middle efficiency. The results of temporal and spatial evolution reveal that the number of cities with a high ULGUE is increasing in general but that their spatial characteristics are relatively dispersed. Population density, environmental regulation, industrial structure, technology input, and the intensity of urban land investment all have major beneficial effects on ULGUE, whereas urban economic development level and urban land use scale clearly have inhibitory effects. In light of the previous conclusions, some recommendations are made to continuously improve ULGUE.