基于广义迪氏指数分解法(Generalized Divisia Index Method,GDIM),利用长江流域绿色创新专利数据,分解各驱动因素对绿色技术创新的贡献率;结合不同省市的背景分析驱动因素的变化情况,深入研究不同驱动因素影响绿色技术创新的时空差异...基于广义迪氏指数分解法(Generalized Divisia Index Method,GDIM),利用长江流域绿色创新专利数据,分解各驱动因素对绿色技术创新的贡献率;结合不同省市的背景分析驱动因素的变化情况,深入研究不同驱动因素影响绿色技术创新的时空差异。最后,针对不同地区的主要问题提出政策建议。展开更多
As one of the largest global emitters of sulfur dioxide(SO_(2)),China faces increasing pressure to achieve sustainable economic and social development.Using panel data of 58 prefecture-level cities in North China betw...As one of the largest global emitters of sulfur dioxide(SO_(2)),China faces increasing pressure to achieve sustainable economic and social development.Using panel data of 58 prefecture-level cities in North China between 2003 and 2017,this paper considers the dynamic spatio-temporal characteristics of industrial SO_(2) emissions in the"2+26"in North China and extended cities in North China and decomposes the determinants of industrial SO_(2) emissions into eight effects using the Generalized Divisia Index Model(GDIM).The contributions of each effect on changes in emissions are assessed on regional,provincial,and prefectural levels,as well as according to various stages.The results indicate the following.First,industrial SO2 emissions in the"2+26"cities in North China and extended cities in North China exhibit spatial autocorrelation and agglomeration effects.Cities with high-high(HH)and low-low(LL)agglomeration patterns were concentrated in Shanxi and Henan provinces,respectively.Second,industrialization,energy consumption,and economic development were the main factors that increased industrial SO2 emissions,while technology,energy sulfur intensity,and economic sulfur intensity were the key factors that reduced them.Third,13 cities,induding Tangshan,were the most important regions where further emissions regulations need to be implemented.These cities were divided into three types and different corresponding measures for reducing their emissions are suggested.Based on the conclusions of this study,this paper puts forward some targeted policy recommendations for reducing industrial SO_(2) emissions according to different categories of cities.展开更多
文摘基于广义迪氏指数分解法(Generalized Divisia Index Method,GDIM),利用长江流域绿色创新专利数据,分解各驱动因素对绿色技术创新的贡献率;结合不同省市的背景分析驱动因素的变化情况,深入研究不同驱动因素影响绿色技术创新的时空差异。最后,针对不同地区的主要问题提出政策建议。
基金the financial support from the National Natural Science Foundation of China[Grant number.72074183,Grant number.71403120]the Humanities and Social Science Foundation of Chinese Ministry of Education[Grant number.20YJC630104]+1 种基金the National Social Science Foundation of China[Grant number.18ZDA052]the Fundamental Research Funds for the Central Universities[Grant number.JBK2007186].
文摘As one of the largest global emitters of sulfur dioxide(SO_(2)),China faces increasing pressure to achieve sustainable economic and social development.Using panel data of 58 prefecture-level cities in North China between 2003 and 2017,this paper considers the dynamic spatio-temporal characteristics of industrial SO_(2) emissions in the"2+26"in North China and extended cities in North China and decomposes the determinants of industrial SO_(2) emissions into eight effects using the Generalized Divisia Index Model(GDIM).The contributions of each effect on changes in emissions are assessed on regional,provincial,and prefectural levels,as well as according to various stages.The results indicate the following.First,industrial SO2 emissions in the"2+26"cities in North China and extended cities in North China exhibit spatial autocorrelation and agglomeration effects.Cities with high-high(HH)and low-low(LL)agglomeration patterns were concentrated in Shanxi and Henan provinces,respectively.Second,industrialization,energy consumption,and economic development were the main factors that increased industrial SO2 emissions,while technology,energy sulfur intensity,and economic sulfur intensity were the key factors that reduced them.Third,13 cities,induding Tangshan,were the most important regions where further emissions regulations need to be implemented.These cities were divided into three types and different corresponding measures for reducing their emissions are suggested.Based on the conclusions of this study,this paper puts forward some targeted policy recommendations for reducing industrial SO_(2) emissions according to different categories of cities.
