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
SDA (Structural Decomposition Analysis) model was applied to analyze the driving factors of embodied carbon and SO_(2) emissions transferred in Shanxi during 2007-2012 based on the input-output model from the perspect...SDA (Structural Decomposition Analysis) model was applied to analyze the driving factors of embodied carbon and SO_(2) emissions transferred in Shanxi during 2007-2012 based on the input-output model from the perspectives of region and industry.The results showed that the change of embodied carbon emissions and embodied SO_(2) emissions of Shanxi and other regions were hindered by the carbon (sulfur) emissions strength effect,but promoted by the intermediate (final) demand scale effect,the intermediate (final) structure effect and the input-output structure effect.The carbon emissions strength effect had a significant contribution to reducing the embodied carbon emissions transferred from industries in Shanxi to other regions.The intermediate (final) demand scale effect was the driving factor to increase the embodied carbon emissions transferred from industries in Shanxi to other regions.The sulfur emissions strength effect was the only factor that reduced the embodied SO_(2) emissions transferred from Shanxi to other industries.The change of embodied carbon emissions from industries in other regions to Shanxi was hindered by the carbon emissions strength effect,but the input-output structure effect and final demand scale effect both increased the embodied carbon emissions from industries in other regions to Shanxi.The change of the embodied SO_(2) emissions transferred from industries in other regions to Shanxi was inhibited by the sulfur emissions strength effect,but the input-output structure effect,the intermediate demand structure effect and the final demand scale effect were both the driving force effect of increasing the embodied SO_(2) emissions transferred from industries in other regions to Shanxi.The corresponding suggestions and measures were put forward.展开更多
Using China’s regional input–output table,the paper constructs indicators of manufacturing servitization,matches manufacturing servitization at the regional level with city data,and uses spatial econometrics to empi...Using China’s regional input–output table,the paper constructs indicators of manufacturing servitization,matches manufacturing servitization at the regional level with city data,and uses spatial econometrics to empirically analyze the impact of manufacturing servitization on urban sulfur dioxide(SO_(2))emissions within the classical Environmental Kuznets Curve(EKC)framework.The results show that manufacturing servitization can reduce SO_(2) emissions.Producer servitization and consumptive services can both significantly reduce industrial SO_(2) emissions.Transportation and warehousing servitization,information servitization,leasing,and commercial servitization,technology research and development servitization significantly reduce SO_(2) emissions;technology research and development servitization,in particular,have the largest influence coefficient,while the reduction effect of servitization in the wholesale and retail and finance sectors is not significant.The study also found that servitization reduced the SO_(2) emissions through technological innovation and industrial structure upgrading.展开更多
This study aims to analysis the influence of economic growth(EG)and energy consumption(EC)on sulfur dioxide emissions(SE)in China.Accordingly,this study explores the link between EG,EC,and SE for 30 provinces in China...This study aims to analysis the influence of economic growth(EG)and energy consumption(EC)on sulfur dioxide emissions(SE)in China.Accordingly,this study explores the link between EG,EC,and SE for 30 provinces in China over the span of 2000-2019.This study also analyzes cross-sectional dependence tests,panel unit root tests,Westerlund panel cointegration tests,Dumitrescu-Hurlin(D-H)causality tests.According to the test results,there is an inverted U-shaped association between EG and SE,and the assumption of the Environmental Kuznets Curve(EKC)is verified.The signs of EG and EC in the fixed effect(FE)and random effect(RE)methods are in line with those in the dynamic ordinary least squares(DOLS),fully modified ordinary least squares(FMOLS)and autoregressive distributed lag(ARDL)estimators.Moreover,the results verified that EC can obviously positive impact the SE.To reduce SE in China,government and policymakers can improve air quality by developing cleaner energy sources and improving energy efficiency.This requires the comprehensive use of policies,regulations,economic incentives,and public participation to promote sustainable development.展开更多
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.
文摘SDA (Structural Decomposition Analysis) model was applied to analyze the driving factors of embodied carbon and SO_(2) emissions transferred in Shanxi during 2007-2012 based on the input-output model from the perspectives of region and industry.The results showed that the change of embodied carbon emissions and embodied SO_(2) emissions of Shanxi and other regions were hindered by the carbon (sulfur) emissions strength effect,but promoted by the intermediate (final) demand scale effect,the intermediate (final) structure effect and the input-output structure effect.The carbon emissions strength effect had a significant contribution to reducing the embodied carbon emissions transferred from industries in Shanxi to other regions.The intermediate (final) demand scale effect was the driving factor to increase the embodied carbon emissions transferred from industries in Shanxi to other regions.The sulfur emissions strength effect was the only factor that reduced the embodied SO_(2) emissions transferred from Shanxi to other industries.The change of embodied carbon emissions from industries in other regions to Shanxi was hindered by the carbon emissions strength effect,but the input-output structure effect and final demand scale effect both increased the embodied carbon emissions from industries in other regions to Shanxi.The change of the embodied SO_(2) emissions transferred from industries in other regions to Shanxi was inhibited by the sulfur emissions strength effect,but the input-output structure effect,the intermediate demand structure effect and the final demand scale effect were both the driving force effect of increasing the embodied SO_(2) emissions transferred from industries in other regions to Shanxi.The corresponding suggestions and measures were put forward.
基金funded by the National Social Science Foundation of China[Grant No.23CGJ011 and Grant No.22BGJ029]National Natural Science Foundation of China[Grant No.72263015]Science and Technology Youth Project of the Jiangxi Provincial Department of Education[Grant No.GJJ200530].
文摘Using China’s regional input–output table,the paper constructs indicators of manufacturing servitization,matches manufacturing servitization at the regional level with city data,and uses spatial econometrics to empirically analyze the impact of manufacturing servitization on urban sulfur dioxide(SO_(2))emissions within the classical Environmental Kuznets Curve(EKC)framework.The results show that manufacturing servitization can reduce SO_(2) emissions.Producer servitization and consumptive services can both significantly reduce industrial SO_(2) emissions.Transportation and warehousing servitization,information servitization,leasing,and commercial servitization,technology research and development servitization significantly reduce SO_(2) emissions;technology research and development servitization,in particular,have the largest influence coefficient,while the reduction effect of servitization in the wholesale and retail and finance sectors is not significant.The study also found that servitization reduced the SO_(2) emissions through technological innovation and industrial structure upgrading.
文摘This study aims to analysis the influence of economic growth(EG)and energy consumption(EC)on sulfur dioxide emissions(SE)in China.Accordingly,this study explores the link between EG,EC,and SE for 30 provinces in China over the span of 2000-2019.This study also analyzes cross-sectional dependence tests,panel unit root tests,Westerlund panel cointegration tests,Dumitrescu-Hurlin(D-H)causality tests.According to the test results,there is an inverted U-shaped association between EG and SE,and the assumption of the Environmental Kuznets Curve(EKC)is verified.The signs of EG and EC in the fixed effect(FE)and random effect(RE)methods are in line with those in the dynamic ordinary least squares(DOLS),fully modified ordinary least squares(FMOLS)and autoregressive distributed lag(ARDL)estimators.Moreover,the results verified that EC can obviously positive impact the SE.To reduce SE in China,government and policymakers can improve air quality by developing cleaner energy sources and improving energy efficiency.This requires the comprehensive use of policies,regulations,economic incentives,and public participation to promote sustainable development.
