In this article, per capita urban carbon emissions were decomposed into manufacturing,transportation, and construction sectors using logarithmic mean Divisia index(LMDI)method. This new decomposition method can provid...In this article, per capita urban carbon emissions were decomposed into manufacturing,transportation, and construction sectors using logarithmic mean Divisia index(LMDI)method. This new decomposition method can provide information about specific drivers of carbon emissions, including urban growth and resident living standards, rather than general demographic and economic factors identified by traditional methods. Using four Chinese megacities(Beijing, Tianjin, Shanghai, and Chongqing) as case studies, we analyzed the factors that influenced per capita carbon emissions from 2010 to 2015. The results showed that per capita carbon emissions increased in Tianjin and Chongqing whereas decreased in Beijing and Shanghai, and that manufacturing was a key driving force. In these four megacities,energy conservation strategies were successfully implemented despite poor energy structure optimization during 2010–2015. Development of manufacturing and improvement of resident living standards in the cities led to an increase in carbon emissions. The unique dual-core urban form of Tianjin might mitigate the increased carbon emissions caused by the transportation sector. Reductions in carbon emissions could be achieved by further optimizing energy structures, limiting the number of private cars, and controlling per capita construction.展开更多
基金supported by the National Key Research & Development Program of China (No.2017YFF0207302)the National Natural Science Foundation of China (Nos.71573242 and 71273252)
文摘In this article, per capita urban carbon emissions were decomposed into manufacturing,transportation, and construction sectors using logarithmic mean Divisia index(LMDI)method. This new decomposition method can provide information about specific drivers of carbon emissions, including urban growth and resident living standards, rather than general demographic and economic factors identified by traditional methods. Using four Chinese megacities(Beijing, Tianjin, Shanghai, and Chongqing) as case studies, we analyzed the factors that influenced per capita carbon emissions from 2010 to 2015. The results showed that per capita carbon emissions increased in Tianjin and Chongqing whereas decreased in Beijing and Shanghai, and that manufacturing was a key driving force. In these four megacities,energy conservation strategies were successfully implemented despite poor energy structure optimization during 2010–2015. Development of manufacturing and improvement of resident living standards in the cities led to an increase in carbon emissions. The unique dual-core urban form of Tianjin might mitigate the increased carbon emissions caused by the transportation sector. Reductions in carbon emissions could be achieved by further optimizing energy structures, limiting the number of private cars, and controlling per capita construction.
