Forecasting national CO2 emissions worldwide

被引:0
作者
Costantini, Lorenzo [1 ,2 ]
Laio, Francesco [2 ]
Mariani, Manuel Sebastian [3 ,4 ]
Ridolfi, Luca [2 ]
Sciarra, Carla [2 ]
机构
[1] CENTAI, Turin, Italy
[2] Politecn Torino, DIATI, I-10129 Turin, Italy
[3] Univ Zurich, URPP Social Networks, CH-8050 Zurich, Switzerland
[4] Univ Elect Sci & Technol China, Inst Fundamental & Frontier Sci, Chengdu 611731, Peoples R China
来源
SCIENTIFIC REPORTS | 2024年 / 14卷 / 01期
关键词
ENVIRONMENTAL KUZNETS CURVE; ECONOMIC-GROWTH; CARBON EMISSION; ENERGY; SUSTAINABILITY; ELECTRICITY; HYPOTHESIS; INNOVATION; INERTIA; IMPACT;
D O I
10.1038/s41598-024-73060-0
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Urgent climate action, especially carbon emissions reduction, is required to achieve sustainable goals. Therefore, understanding the drivers of and predicting CO2 emissions is a compelling matter. We present two global modeling frameworks-a multivariate regression and a Random Forest Regressor (RFR)-to hindcast (until 2021) and forecast (up to 2035) CO2 emissions across 117 countries as driven by 12 socioeconomic indicators regarding carbon emissions, economic well-being, green and complexity economics, energy use and consumption. Our results identify key driving features to explain emissions pathways, where beyond-GDP indicators rooted in the Economic Complexity field emerge. Considering current countries' development status, divergent emission dynamics appear. According to the RFR, a - 6.2% reduction is predicted for developed economies by 2035 and a + 19% increase for developing ones (referring to 2020), thus stressing the need to promote green growth and sustainable development in low-capacity contexts.
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页数:14
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