Regression analysis and driving force model building of CO2 emissions in China

被引:1
|
作者
Zhou, Yi [1 ]
Zhang, Jinyan [2 ]
Hu, Shanying [1 ]
机构
[1] Tsinghua Univ, Dept Chem Engn, Ctr Ind Ecol, Beijing, Peoples R China
[2] Tsinghua Univ, PBC Sch Finance, Beijing, Peoples R China
关键词
PRIMARY ENERGY DEMAND; DRIVERS; FUTURE;
D O I
10.1038/s41598-021-86183-5
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
In recent years, global warming has become increasingly devastating, leading to severe consequences, such as extreme weather events and sea-level rise. To reduce carbon dioxide emissions, it is essential to recognize different emission sources and key driving factors. Three main carbon emission sources from the period between 1990 and 2017 were identified in China: the energy industry, fuel combustion in other industries, and industrial process. For each source, a driving force model was developed via multiple linear regression. Based on these models, forecasts of the carbon intensity and total CO2 emissions were obtained from 2018 to 2030. The results demonstrate that the CO2 emission intensity and total emissions will continue to decrease but more effort will be required to achieve the goal of Paris Agreement.
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页数:14
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