STIRPAT-Based Driving Factor Decomposition Analysis of Agricultural Carbon Emissions in Hebei, China
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Department of Economics and Management, North China Electric Power University, Hebei 071003, China
Submission date: 2017-07-12
Final revision date: 2017-09-20
Acceptance date: 2017-09-21
Online publication date: 2018-02-20
Publication date: 2018-03-30
Corresponding author
Tian Zhao   

Department of Economics and Management´╝îNorth China Electric Power University, Huadian road No.689,Beishi district,Baoding,China, 071003 Baoding, China
Pol. J. Environ. Stud. 2018;27(4):1449-1461
Low-carbon development has recently become a growing trend in agricultural modernization. It will provide beneficial guidance for exploring driving factors of agricultural carbon emissions in Hebei Province, a typical agricultural region, and formulate relevant policy on its reduction. Calculating carbon emissions in Hebei from 1995 to 2014 demonstrated that energy and land use accounted for more than 90% of agricultural carbon emissions, and there was an increasing tendency overall with a peak value in 2010 and, to a certain extent lately, a slight decline. This paper employed transformed Kaya identity in light of local actual conditions for selecting eight influencing factors. Meanwhile, the extended STIRPAT model and ridge regression were used to make regression analysis. Results showed that contributing factors were efficiency, agricultural import, urbanization, agricultural mechanization, and population, whose 1% increase caused 0.1852%, 0.1663%, 0.1597%, 0.1573%, and 0.1329% increases in carbon emissions, respectively, while 1% growth in industry structure and agricultural affluence were responsible for 0.1475%, and changing the elastic coefficient of (0.1314-0.2958lnA)% decrease in carbon emissions, respectively, where A represented agricultural output value per capita. Furthermore, there existed an inverted U-shaped EKC between economic progress and carbon emissions. Given the above conclusions, policy recommendations were provided for effectively achieving agricultural carbon emissions reductions.
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