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
Ambient air quality is an important part of the ecological environment.Based on panel data from 192 countries for the period 2010–2016,our study applies spatial geography elements in a spatial panel model to analyze ...Ambient air quality is an important part of the ecological environment.Based on panel data from 192 countries for the period 2010–2016,our study applies spatial geography elements in a spatial panel model to analyze whether PM_(2.5)harms residents'health.We find a positive correlation between PM_(2.5)concentration and the prevalence of tuberculosis.Empirical testing shows that if residents live in environments with high PM_(2.5)concentrations for an extended period,it increases their probability of contracting tuberculosis.PM_(2.5)concentration and economic growth have an environmental Kuznets curve(EKC)relationship.Furthermore,PM_(2.5)concentration and prevalence of tuberculosis in different countries have a positive spatial correlation during the study period.The values of PM_(2.5)concentration in adjacent areas are similar,because PM_(2.5)can cross borders through airflow and as economic development levels in adjacent regions are similar.When regulating haze pollution,we should adopt regional joint governance,consider the specific characteristics of different regions,and coordinate these regulations with environmental protection policies to realize the goal of“lucid waters and lush mountains.”展开更多
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.
基金supported by the Fujian Provincial Social Science Foundation of China“Study on Social Welfare Measurement and Effective Mechanism of Land Finance in Fujian Province”[Grant number:.FJ2018C042].
文摘Ambient air quality is an important part of the ecological environment.Based on panel data from 192 countries for the period 2010–2016,our study applies spatial geography elements in a spatial panel model to analyze whether PM_(2.5)harms residents'health.We find a positive correlation between PM_(2.5)concentration and the prevalence of tuberculosis.Empirical testing shows that if residents live in environments with high PM_(2.5)concentrations for an extended period,it increases their probability of contracting tuberculosis.PM_(2.5)concentration and economic growth have an environmental Kuznets curve(EKC)relationship.Furthermore,PM_(2.5)concentration and prevalence of tuberculosis in different countries have a positive spatial correlation during the study period.The values of PM_(2.5)concentration in adjacent areas are similar,because PM_(2.5)can cross borders through airflow and as economic development levels in adjacent regions are similar.When regulating haze pollution,we should adopt regional joint governance,consider the specific characteristics of different regions,and coordinate these regulations with environmental protection policies to realize the goal of“lucid waters and lush mountains.”
