The study on greenhouse gas inventory in urban China lags far behind the global level. The important factor that curbs the carbon inventory of cities of China is inventory methodology and scope. Given the insufficienc...The study on greenhouse gas inventory in urban China lags far behind the global level. The important factor that curbs the carbon inventory of cities of China is inventory methodology and scope. Given the insufficiency of Chinese cities carbon inventory, a system and accounting model （scopel＋ scope2） as well as principles and boundaries were proposed for China. The carbon emissions in scopel and scopel＋ scope2 were calculated in Chinese prefecture-level cities. The EDGAR dataset was used for the calculation of scopel carbon emissions in cities in China and the level of uncertainty was analyzed as well. The results showed that the direct carbon emission of cities in China was about 31.65% of China total emissions. The scopel＋ scope2 carbon emissions in cities of China were calculated based on the GIS and RS model. The results showed that the sum of direct （scopel） and indirect （scope2） carbon emissions of cities in China accounted for 38.80% of total China carbon emissions.展开更多
Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon e...Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.展开更多
文摘The study on greenhouse gas inventory in urban China lags far behind the global level. The important factor that curbs the carbon inventory of cities of China is inventory methodology and scope. Given the insufficiency of Chinese cities carbon inventory, a system and accounting model （scopel＋ scope2） as well as principles and boundaries were proposed for China. The carbon emissions in scopel and scopel＋ scope2 were calculated in Chinese prefecture-level cities. The EDGAR dataset was used for the calculation of scopel carbon emissions in cities in China and the level of uncertainty was analyzed as well. The results showed that the direct carbon emission of cities in China was about 31.65% of China total emissions. The scopel＋ scope2 carbon emissions in cities of China were calculated based on the GIS and RS model. The results showed that the sum of direct （scopel） and indirect （scope2） carbon emissions of cities in China accounted for 38.80% of total China carbon emissions.
基金National Natural Science Foundation of China,No.41601151Guangdong Natural Science Foundation,No.2016A030310149
文摘Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.
