RESUMEN
One of the challenges that China currently faces is how to reduce the emissions of water pollution. However, the study of water pollution convergence has a certain policy significance for controlling the emissions of water pollution. This article firstly uses chemical oxygen demand (COD) and ammonia nitrogen (NH3-N) as indicators of water pollution. Due to the obvious spillover effect of water in space, this article adds a spatial effect to the convergence model. Based on panel data of 30 provinces and cities from 2006 to 2017, this article uses a dynamic spatial Dubin model to analyze the convergence of water pollution emission intensity to address the endogenous problem in the model. The empirical results of this paper show that there is absolute ß-convergence and conditional ß-convergence in the intensity of water pollution emissions. The spatial autocorrelation test shows that there is a positive spatial autocorrelation of water pollution emissions, which means that the pollution emissions in neighboring areas will affect the emissions in the local area. The industrial structure has a certain promoting effect on the emission of water pollution, which means that adjusting the industrial structure and alleviating the structure of the secondary industry is the trend of future development. Economic growth can curb the emissions of water pollution. The influences of urbanization and foreign investment on the emissions of the two pollutants are inconsistent, and policies can be formulated according to local conditions in the future.
Asunto(s)
Desarrollo Económico , Contaminación del Agua , China , Ciudades , UrbanizaciónRESUMEN
With the rapid development of China, urbanization has become an important research topic of China's CO2 emissions. To fill the gap in considering the spatial correlation of the comprehensive urbanization that includes multi-dimensional factors on CO2 emissions from urban civil buildings (UBEC), this study constructs a comprehensive evaluation indicator of urbanization from four aspects including population, economy, society, and land urbanization by using the entropy method. The spatial spillover effect of UBEC and the impact of comprehensive urbanization on UBEC are also studied by using the spatial panel model in this paper. This study finds out that UBEC has obvious spatial spillover effects. During the early years of the study period, the eastern coastal areas had greater carbon emissions, while in recent years, they have gradually transitioned to the northwestern regions. Comprehensive urbanization has a significant promotion effect on it. And foreign direct investment and per capita energy consumption also have positive impact on UBEC. This study provides a reference for measuring the effects of urbanization on sector-specific CO2 emissions and may be useful for energy efficiency and emission abatement efforts in China.