Measurement and spatial-temporal analysis of coupling coordination development between green finance and environmental governance in China.

To direct financial resources for achieving the goal of sustainable development, Chinese government has devoted increasing efforts to developing green finance. However, few studies explored the relationship between green finance and environmental governance. Thus, this paper first theoretically discusses the interactive connection between green finance and environmental governance. And then we construct two comprehensive indicator systems and use entropy method to calculate green finance index (GFI) and environmental governance index (EGI) for 30 provinces of China from 2004 to 2020. The theoretical analysis unveils the complementary and mutual reinforcing relationship of the interaction between green finance and environmental governance through green industry. Using the data of GFI and EGI, the coupling coordination degree of green finance and environmental governance (CCDGE) is measured by coupling coordination model. The trend analysis discovers that GFI is increasing over time while EGI starts decreasing from 2013. Although GFI has grown more rapidly than EGI, but the development of green finance still lags behind environmental governance because of its short history. Just because of the uncoordinated development between green finance and environmental governance, CCDGE has been hovering in the moderate coupling coordination stage for a long time and still has a great distance to the high coupling coordination level. These findings imply that the relationship between green finance and environmental governance is still in a state of disorderly development that restricts each other. Furthermore, the findings of spatial-temporal analysis show there are obvious regional differences in GFI and EGI and the interactive effect between green finance and environmental governance. Specifically, GFI and EGI in eastern China are the highest, while CCDGE presents with a ladder decline status of "eastern region > central region > northeast region > west region." Our findings provide vital references for policymakers to promote the coupling coordination development between green finance and environmental governance.

Spatial distribution and regional difference of carbon emissions efficiency of industrial energy in China.

The three-stage super-efficiency slack-based measure and data envelopment analysis (SBM-DEA) model with undesirable outputs is used to calculate carbon emissions efficiency of industrial energy (CEEIE) of 30 provinces in China from 2000 to 2017. Then ArcGIS software is used to illustrate the spatial distribution of CEEIE, and Dagum Gini ratio is calculated to decompose the regional difference. The results show that the spatial distribution of CEEIE changes from disorder to order and provinces characterized with high or low CEEIE cluster in space over time. The total Dagum Gini coefficient indicates that the interprovincial difference in CEEIE across China is gradually expanding, which is mainly induced by the difference between regions. Our findings attach more importance to interregional integration policies for carbon emissions reduction in China.

Repeated biotransformation of glycerol to 1,3-dihydroxyacetone by immobilized cells of Gluconobacter oxydans with glycerol- and urea-feeding strategy in a bubble column bioreactor.

Some inorganic nitrogen sources and amino acids instead of yeast extract, which resulted in trouble of product purification, were introduced for 1,3-dihydroxyacetone (DHA) production by biotransformation with Gluconobacter oxydans. The results showed that urea is an optimal nitrogen source. Furthermore, the effects of glycerol- and urea-feeding strategies for DHA production by immobilized cells in a home-made bubble column bioreactor were optimized. Cells immobilization was prepared by cultivation in the bioreactor packed with porous ceramics, and then the broth was removed. Then, repeated biotransformation by continuous-feeding of glycerol and urea was developed. Up to 96.4±4.1g/L of average DHA concentration with 94.8±2.2% of average conversion rate of glycerol to DHA was achieved after 12 cycles of run. Near colorless DHA solution with few impurities was obtained and the production cost could be decreased.