期刊
ENERGY ECONOMICS
卷 81, 期 -, 页码 393-407出版社
ELSEVIER
DOI: 10.1016/j.eneco.2019.04.012
关键词
Natural gas consumption; CO2 emissions; Nonparametric additive regression model
类别
资金
- State Grid Corporation technology project (WBS) [521104170015]
- Ministry of Education of China [10JBG013]
- China National Social Science Fund [17AZD013]
- National Natural Science Foundation of China [71463020, 61563018, 71563014]
- Jiangxi Natural Science Foundation of Jiangxi Province [2018ACB29002, 20181BAB201011]
China is now the world's largest emitter of carbon dioxide (CO2), thus leading to China facing enormous pressure on CO2 emission reduction. Natural gas is a high thermal and low-emission energy. Expanding natural gas consumption cannot only meet the growing demand for energy consumption but also optimize energy consumption structure. Therefore, many scholars have investigated the effect of natural gas consumption on CO2 emissions. However, ignoring a large number of nonlinear relationships between economic variables, the vast majority of existing studies use traditional linear models to explore the relationships between natural gas consumption and CO2 emissions. In order to make up for the gap in existing research, this paper uses the nonparametric additive regression model with data-driven features to investigate the relationships between the two. The results show that natural gas consumption has an inverted U-shaped nonlinear effect on CO2 emissions in the eastern region, but a positive U-shaped nonlinear effect in the central and western regions. The linear impact of natural gas consumption on CO2 emissions in the eastern and central regions is higher than that in the western region, due to the differences in resource availability and energy prices, as well as natural gas consumption. Therefore, during the process of promoting natural gas consumption, the central and local governments should adopt heterogeneous measures at different stages of development. (C) 2019 Elsevier B.V. All rights reserved.
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