中国区域能源效率对霾污染的空间效应——基于空间杜宾模型的实证分析
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摘要
以中国29个省市自治区为研究对象,并以2001～2015年PM_(2.5)年度均值作为衡量霾污染的指标,构建了全要素能源效率对中国霾污染影响的空间杜宾模型.研究表明:中国绝大部分省市的霾污染演变趋势具有倒"U"的特点,这说明中国的霾污染在2001～2015年间经历了先上升后下降的总体变化趋势;无论是采用地理相邻权重还是经济权重,中国省际间的霾污染均存在显著空间集聚效应,这揭示霾污染的治理与控制需要地区间建立恰当的合作机制,避免出现"损人利己"现象;在对一系列经济社会因素控制的基础上,全要素能源效率对霾污染存在显著的负向影响并且具有显著的空间溢出效应,这表明全要素能源效率的提高不仅会显著降低本地区的霾污染水平,还将对周边地区的霾污染产生显著的负向影响;分解方程结果显示,技术进步和技术效率对霾污染的负向效应显著,并且技术进步的直接效应大于技术效率,但两者的间接效应均显著大于直接效应,这揭示了技术扩散对霾污染具有重要的潜在促降效应.因此,在治理霾污染的过程中,要通过不断优化能源结构和开发新能源技术以发挥全要素能源效率的减霾效果,以及通过地区间的交流与合作发挥技术扩散效应在霾污染治理中的作用.
A new spatial Durbin model was built to study the impact of total factor energy efficiency(TFEE) on haze pollution in China. The built model was utilized to analyze the PM_(2.5) data of 29 provinces in China during 2001～2015. The results showed that the haze pollution in most of provinces presented a reverse "U" shape and the development trend of the haze pollution was decreasing. No matter the geographical neighboring weights or the economic weights were considered, there existed a significant spatial agglomeration effect in the haze pollution between the provinces of China. In addition, when controlling other factors, the TFEE was found to have a significant negative and spatial spillover effect on the haze pollution. It showed that improving the TFEE would not only reduce the haze pollution of local regions but also had a significantly negative impact on the haze pollution of their neighbors. From the results of decomposition of the TFEE, it was found that the technical progress and the technical efficiency both have significantly negative impacts on the haze pollution. It was also observed that the technological progress had greater direct effect than the technological efficiency, but the indirect effects of both were significantly greater than the direct effects of both. This revealed that technology diffusion played an important potential role for the haze pollution. In conclusion, to promote the potential effect of the TFEE in tackling the haze pollution, it would be very important to optimize industrial structure, explore new energy technology and strengthen the exchanges and cooperation in technology among regions.
A new spatial Durbin model was built to study the impact of total factor energy efficiency(TFEE) on haze pollution in China. The built model was utilized to analyze the PM_(2.5) data of 29 provinces in China during 2001～2015. The results showed that the haze pollution in most of provinces presented a reverse "U" shape and the development trend of the haze pollution was decreasing. No matter the geographical neighboring weights or the economic weights were considered, there existed a significant spatial agglomeration effect in the haze pollution between the provinces of China. In addition, when controlling other factors, the TFEE was found to have a significant negative and spatial spillover effect on the haze pollution. It showed that improving the TFEE would not only reduce the haze pollution of local regions but also had a significantly negative impact on the haze pollution of their neighbors. From the results of decomposition of the TFEE, it was found that the technical progress and the technical efficiency both have significantly negative impacts on the haze pollution. It was also observed that the technological progress had greater direct effect than the technological efficiency, but the indirect effects of both were significantly greater than the direct effects of both. This revealed that technology diffusion played an important potential role for the haze pollution. In conclusion, to promote the potential effect of the TFEE in tackling the haze pollution, it would be very important to optimize industrial structure, explore new energy technology and strengthen the exchanges and cooperation in technology among regions.
引文
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[2]潘慧峰,王鑫,张书宇.雾霾污染的持续性及空间溢出效应分析--来自京津冀地区的证据[J].中国软科学,2015,(12):134-143.Pan H,Wang X,Zhang S.Duration and spatial spillover effects of haze pollution-evidence from Beijing-Tianjin-Hebei region[J].China Soft Science,2015,(12):134-143.
[3]向堃,宋德勇.中国省域PM2.5污染的空间实证研究[J].中国人口?资源与环境,2015,25(9):153-159.Xiang K,Song D.Spatial analysis of China’s PM2.5 pollution at the provincial level[J].China Population,Resources and Environment,2015,25(9):153-159.
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[5]刘华军,裴延峰.中国雾霾污染的环境库兹涅茨曲线检验[J].统计研究,2017,34(3):45-54.Liu H,Pei Y.An Empirical test of the environmental kuznets curve of China’s haze pollution[J].Statistical Research,2017,34(3):45-54.
[6]冷艳丽,冼国明,杜思正.外商直接投资与雾霾污染--基于中国省际面板数据的实证分析[J].国际贸易问题,2015,(12):74-84.Leng Y,Xian G,Du S.Foreign direct investment and haze pollution:An empirical analysis based on provincial panel data[J].Journal of International Trade,2015,(12):74-84.
[7]李力,唐登莉,孔英,等.FDI对城市雾霾污染影响的空间计量研究--以珠三角地区为例[J].管理评论,2016,28(6):11-24.Li L,Tang D,Kong Y,et al.Spatial economic analysis of impact of FDI on urban haze pollution-Case of the Pearl River Delta region[J].Management Review,2016,28(6):11-24.
[8]李名升,任晓霞,于洋,等.中国大陆城市PM2.5污染时空分布规律[J].中国环境科学,2016,36(3):641-650.Li M,Ren X,Yu Y,et al.Spatiotemporal pattern of ground-level fine particular matter PM2.5 pollution in mainland China[J].China Environmental Science,2016,36(3):641-650.
[9]郭婷,朱彬,康志明,等.1960~2012年长江三角洲地区雾日与霾日的气候特征及其影响因素[J].中国环境科学,2016,36(4):961-969.Guo T,Zhu B,Kang Z,et al.Spatial and temporal distribution Characteristic of fog days and haze days from 1960~2012and impact factors over the Yangtze River Delta Region[J].China Environmental Science,2016,36(4):961-969.
[10]张云伟,王晴茹,陈嘉,等.城市街谷内PM2.5浓度时空变化及影响因素分析[J].中国环境科学,2016,36(10):2944-2949.Zhang Y,Wang Q,Chen J,et al.Temporal and spatial characteristic of pm2.5concentration in urban street canyons and analysis on the affecting factors[J].China Environmental Science,2016,36(10):2944-2949.
[11]王琴,张大伟,刘保献,等.基于PMF模型的北京市PM2.5来源的时空分布特征[J].中国环境科学,2015,35(10):2917-2924.Wang Q,Zhang D,Liu B,et al.Spatial and temporal variations of ambient PM2.5 source contributions using positive matrix factorization[J].China Environmental Science,2015,35(10):2917-2924.
[12]马丽梅,刘生龙,张晓.能源结构、交通模式与雾霾污染--基于空间计量模型的研究[J].财贸经济,2016,37(1):147-160.Ma L,Liu S,Zhang X.Study on haze pollution induced by energy structure and transportation:Based on spatial econometric model analysis[J].Finance&Trade Economics,2016,37(1):147-160.
[13]冷艳丽,杜思正.能源价格扭曲与雾霾污染--中国的经验证据[J].产业经济研究,2016,(1):71-79.Leng Y,Du S.Energy price distortion and haze pollution:The evidence from China[J].Industrial Economics Research,2016,(1):71-79.
[14]秦蒙,刘修岩,仝怡婷.蔓延的城市空间是否加重了雾霾污染--来自中国PM2.5数据的经验分析[J].财贸经济,2016,37(11):146-160.Qin M,Liu X,Tong Y.Does urban sprawl exacerbate haze pollutionAn empirical study of fine particles PM2.5 in Chinese city[J].Finance&Trade Economics,2016,37(11):146-160.
[15]黄寿峰.财政分权对中国雾霾影响的研究[J].世界经济,2017,40(2):127-152.Huang S.A study of empirical of fiscal decentralization on smog pollution[J].The Journal of World Economy,2017,40(2):127-152.
[16]李根生,韩民春.财政分权、空间外溢与中国城市雾霾污染:机理与证据[J].当代财经,2015,(6):26-34.Li G,Han M.Fiscal decentralization,spatial spillover and China’s urban haze pollution:mechanism and evidences[J].Contemporary Finance&Economics,2015,(6):26-34.
[17]Guan D,Su X,Zhang Q,et al.The socioeconomic drivers of China’s primary PM2.5 emissions[J].Environmental Research Letters,2014,9(2):024010.
[18]王立平,陈俊.中国雾霾污染的社会经济影响因素--基于空间面板数据EBA模型实证研究[J].环境科学学报,2016,36(10):3833-3839.Wang L,Chen J.Socio-economic influential factors of haze pollution in China:Empirical Study by EBA model using spatial panel data[J].Acta Scientiate Circumstantiae,2016,36(10):3833-3839.
[19]邵帅,李欣,曹建华,等.中国雾霾污染治理的经济政策选择-基于空间溢出效应的视角[J].经济研究,2016,(9):73-88.Shao S,Li X,Cao J,et al.China’s economic policy choices for governing smog pollution based on spatial spillover effects[J].Economic Research Journal,2016,(9):73-88.
[20]李云燕,殷晨曦.京津冀地区PM2.5减排实效与影响因素的门限效应[J].中国环境科学,2017,37(4):25-32.Li Y,Yin C.Threshold effect of socio-economic factors influencing PM2.5 in Beijing-Tianjin-Hebei[J].China Environmental Science,2017,37(4):25-32.
[21]李国璋,江金荣,周彩云.全要素能源效率与环境污染关系研究[J].中国人口?资源与环境,2010,20(4):50-56.Li G,Jiang J,Zhou C.Relations between total factor energy efficiency and environmental pollution[J].China Population,Resources and Environment,2010,20(4):50-56.
[22]东童童.全要素工业能源效率与雾霾污染的交互影响--以长江经济带为例[J].城市问题,2017,(11):85-93.Dong T.Interactive effect between industrial energy efficiency and haze pollution-Case of the Yangtze River Economic Belt[J].Urban Problems,2017,(11):85-93.
[23]Van D A,Martin R V,Brauer M,et al.Use of satellite observations for long-term exposure assessment of global concentrations of fine particulate matter[J].Environmental Health Perspectives,2015,123(2):135.
[24]Chung Y H,F?re R,Grosskopf S.Productivity and undesirable outputs:A directional distance function approach[J].Microeconomics,1995,51(3):229-240.
[25]Elhorst J.“Spatial Panel Data Models,”Handbook of Applied Spatial Analysis,Springer:Berlin Heidelberg New York,2010a:377-407.
[26]国家统计局.中国统计年鉴[M].北京:中国统计出版社,2002-2016.National Bureau of Statistics.China Statistical Yearbook[M].Beijing:China Statistics Press,2002-2016.
[27]国家统计局.中国科技统计年鉴[M].北京:中国统计出版社,2002-2016.National Bureau of Statistics.China Statistical Yearbook on Science and Technology[M].Beijing:China Statistics Press,2002-2016.
[28]国家统计局.中国环境统计年鉴[M].北京:中国统计出版社,2002-2016.National Bureau of Statistics.China Statistical Yearbook on Environment[M].Beijing:China Statistics Press,2002-2016.
[29]国家统计局.中国能源统计年鉴[M].北京:中国统计出版社,2002-2016.National Bureau of Statistics.China Energy Statistical Yearbook[M].Beijing:China Statistics Press,2002-2016.
[30]国家统计局.中国经济普查年鉴[M].北京:中国统计出版社,2002-2016.National Bureau of Statistics.China Economic Census Yearbook[M].Beijing:China Statistics Press,2002-2016.
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