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 the operation phase of 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 maybe useful for energy efficiency and emission abatement efforts in China.
One of the challenges that China currently faces is how to reduce the emissions of the water pollution. However, the study of water pollution convergence has certain policy significance for controlling the emissions of water pollution. This article firstly uses chemical oxygen demand(COD)and ammonia nitrogen(NH 3 -N)as indicators of water pollution. Due to the obvious spillover effect of water in space, this article adds 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 resultsof this paper show that there is absolute -convergence and conditional -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.
Abstract. In this paper, an effective model is constructed to discuss the sustainability of a country. We define Coordination Coefficient (CC) to measure the sustainability of a country or a policy and use the value of CC to define how and when a country is sustainable or unsustainable. To consider all the possible parameters connected to the sustainability of a country, we divide them into four aspects: Society, Humanity, Resource and Economy. For each aspect, we use Entropy Method to determine the weight of its parameters. CC is defined by analyzing the mutual influence and restriction between aspects and parameters. The point when CC is zero can be roughly recognized as the demarcation point of sustainability and unsustainability. For more accuracy, cluster is used to determine the demarcation point. To prove the accuracy of the model, we select the countries which need the most support and intervention and introduce the concept "Ecological Footprint" to measure their sustainability and ecological demands. Then we use Time series prediction is used to predict the exact year when a country will be sustainable.
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