Can Environmental Quality Improvement and Emission Reduction Targets Be Realized Simultaneously? Evidence from China and A Geographically and Temporally Weighted Regression Model.

摘要: The reductions of industrial pollution and greenhouse gas emissions are important actions to create an ecologically stable civilization. However, there few reports on the interaction variation between them. In this study, vertical horizontal scatter degree method is used calculate a comprehensive index emissions. Then based carbon density, geographically temporally weighted regression (GTWR) model developed examine results specify that exists spatial autocorrelation for density in China. Overall, average effect positive. This indicates play driving role whole, while temporal differences interactions at provincial level. According Herfindahl index, neither time nor space can be neglected. Moreover, according traditional division eastern, central western regions China, situation 30 provinces examined. Results show little difference parameter-estimated neighboring provinces. many provinces, pull widespread. Thus, could reduced by controlling more than 60% regions. other regions, such as Shanghai Heilongjiang, do not have density. But due heterogeneity, effects different times. It necessary consider reasons changes combined with factors. Finally, empirical support pertinent suggestions future emissions, optimizing energy mix reinforcing government regulation.