Geographical Detector Model for Influencing Factors of Industrial Sector Carbon Dioxide Emissions in Inner Mongolia, China

Rina Wu, Jiquan Zhang, Yuhai Bao and Feng Zhang
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Rina Wu: College of Environment, Northeast Normal University, Changchun 130024, China
Jiquan Zhang: College of Environment, Northeast Normal University, Changchun 130024, China
Yuhai Bao: Inner Mongolia Key Laboratory of Remote Sensing and Geographic Information, Huhhot 010022, China
Feng Zhang: College of Environment, Northeast Normal University, Changchun 130024, China

Sustainability, 2016, vol. 8, issue 2, 1-12

Abstract: Studying the influencing factors of carbon dioxide emissions is not only practically but also theoretically crucial for establishing regional carbon-reduction policies, developing low-carbon economy and solving the climate problems. Therefore, we used a geographical detector model which is consists of four parts, i.e. , risk detector, factor detector, ecological detector and interaction detector to analyze the effect of these social economic factors, i.e. , GDP, industrial structure, urbanization rate, economic growth rate, population and road density on the increase of energy consumption carbon dioxide emissions in industrial sector in Inner Mongolia northeast of China. Thus, combining with the result of four detectors, we found that GDP and population more influence than economic growth rate, industrial structure, urbanization rate and road density. The interactive effect of any two influencing factors enhances the increase of the carbon dioxide emissions. The findings of this research have significant policy implications for regions like Inner Mongolia.

Keywords: geographical detector model; influencing factors; carbon dioxide emissions; industrial sector (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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