China's energy-related carbon emissions projections for the shared socioeconomic pathways

被引:86
作者
Zhang, Fan [1 ]
Deng, Xiangzheng [1 ]
Xie, Li [2 ,3 ]
Xu, Ning [1 ]
机构
[1] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
[2] Hunan Univ, Sch Econ & Trade, Changsha 410079, Peoples R China
[3] Hunan Univ, Hunan Dev Res Inst, Changsha 410082, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
Carbon emission; Shared socioeconomic pathways (SSPS); In-sample and out-of-sample approach; Forecasting; China; CO2; EMISSIONS; KUZNETS CURVE; PEAK PRIOR; IMPACTS; GROWTH; PERSPECTIVE; CONSUMPTION; TECHNOLOGY; INDUSTRY; ECONOMY;
D O I
10.1016/j.resconrec.2021.105456
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The carbon emissions from China's energy consumption are substantially increasing. In this context, it is necessary to predict the long-term dynamics of China's carbon emissions. Existing research has investigated future scenarios for China's carbon emissions, but there is still no consensus on such issues as the amount of emissions at peak points and the future carbon emissions path over a longer period. This paper aimed to explore the dynamics of China's carbon emissions under five Shared Socioeconomic Pathways scenarios (SSP1-SSP5), and to provide further evidences for the comprehensive analysis and prediction of climate change. Before forecasting the socioeconomic data, an in-sample and out-of-sample approach was used to evaluate the prediction accuracy of the feasible generalized least squares (FGLS) model. By using historical data from 30 provinces, the relationship among population, educational attainment, per capita GDP, and carbon emissions was investigated. Finally, carbon emissions from 2018 to 2100 were predicted based on the settings of different SSP scenarios and model parameters. The results showed that the peak value was 2030 for SSP1 and SSP5, 2029 for SSP2 and SSP4, and 2028 for SSP3. China will reach the largest cumulative carbon emissions amounting to 814.84 billion tons under the SSP5 scenario. Under all the SSP scenarios, the western region was always the first to reach its peak value, followed by the central region and then the eastern coastal zone. From 2018 to 2100, Jiangsu, Shandong, Guangdong, Zhejiang, Henan, Inner Mongolia, Xinjiang, Hebei, Hubei and Sichuan will contribute significantly to total carbon emissions under different SSP scenarios. All the results and conclusions would provide significant contributions for carbon reduction and climate change mitigation.
引用
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页数:11
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