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Energies 2018, 11(6), 1489;

Scenario Analysis of Carbon Emissions of Beijing-Tianjin-Hebei

Department of Economics and Management, North China Electric Power University, Baoding 071003, China
Author to whom correspondence should be addressed.
Received: 4 April 2018 / Revised: 2 June 2018 / Accepted: 4 June 2018 / Published: 7 June 2018
(This article belongs to the Section Energy Sources)
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This paper utilizes the generalized Fisher index (GFI) to decompose the factors of carbon emission and exploits improved particle swarm optimization-back propagation (IPSO-BP) neural network modelling to predict the primary energy consumption CO2 emissions in different scenarios of Beijing-Tianjin-Hebei region. The results show that (1) the main factors that affect the region are economic factors, followed by population size. On the contrary, the factors that mainly inhibit the carbon emissions are energy structure and energy intensity. (2) The peak year of carbon emission changes with the different scenarios. In a low carbon scenario, the carbon emission will have a decline stage between 2015 and 2018, then the carbon emission will be in the ascending phase during 2019–2030. In basic and high carbon scenarios, the carbon emission will peak in 2025 and 2028, respectively. View Full-Text
Keywords: carbon emissions; generalized fisher index; IPSO-BP neural network model; Beijing-Tianjin-Hebei region carbon emissions; generalized fisher index; IPSO-BP neural network model; Beijing-Tianjin-Hebei region

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Zhou, J.; Jin, B.; Du, S.; Zhang, P. Scenario Analysis of Carbon Emissions of Beijing-Tianjin-Hebei. Energies 2018, 11, 1489.

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