Scenario prediction for CO2 emissions in 2020 in Jilin province

doi:10.7523/j.issn.2095-6134.2011.5.008

Abstract

Abstract:

Using the data of population, GDP, and energy intensity in Jilin province from 1978 to 2009 as input data, we use BP neural network to predict carbon dioxide emissions in 2020 in Jilin province under reference and emission mitigation scenarios. The results show that, if we use carbon dioxide emissions per unit of GDP in 2005 in Jilin province as a reference, CO₂ emissions per GDP in 2020 will be reduced by 55.17% and 58.79% under the two scenarios, respectively. The results also show that, if we use the national average level in 2005 as a reference, CO₂ emissions per unit of GDP in 2020 in Jilin province will be reduced by 35.40% and 40.62%, respectively.

Key words: CO₂ emissions, scenario prediction, BP artificial neural network, Jilin province

CLC Number:

ZHANG Ya-Xin, ZHANG Ping-Yu. Scenario prediction for CO₂ emissions in 2020 in Jilin province[J]. , 2011, 28(5): 617-623.

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Scenario prediction for CO₂ emissions in 2020 in Jilin province

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