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Journal of Environmental Biology

pISSN: 0254-8704 ; eISSN: 2394-0379 ; CODEN: JEBIDP

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    Abstract - Issue Jul 2015, 36 (4)                                     Back

nstantaneous and historical temperature effects on a-pinene

How does green technology influence CO2 emission in China? - An empirical research based on provincial data of China


Ding Weina1, Han Botang1*, Zhao Xin1 and Massimiliano Mazzanti2

1School of Management and Economics, Beijing Institute of Technology, Beijing-100081, China

2School of Economics, University of Ferrara, Ferrara, Italy

*Corresponding Author?s Email :




Publication Data

Paper received:

05 June 2014


Revised received:

30 September 2014


Re-revised received:

01 January 2015



07 February 2015



This paper investigates the role of green innovations aimed at reducing carbon dioxide emissions as a factor that compensates for growth and population effects. It has been shown from tests that the positive effect of green innovations on carbon emissions exists within a STIRPAT framework from a local perspective. The panel data is derived from China Statistical Yearbook and China Intellectual Property Office covered from 1999 to 2013. In addition,the static panel model was run to estimate the diversity among three typical regions of China. The main result shows that the green technology change has not played a dominant role yet in promoting environmental protection, while a scale effect (Affluence and Population)still prevails, although green patents show positive influences on the CO2 emission reduction inthe whole country as well as the East and West regions, except the Central region. Moreover, it turns out that the classical EKC hypothesis does stand in China, referring to the three regions with the inverted ?U? shape. The analysis gives suggestions to the policy makers, which would support enlarging the investment scale on green patents and encourage international corporation with environmental related innovations. ??  



 Key words

CO2 Emissions, Green patent, STIRPAT Model, Regional effect 



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