| Literature DB >> 32700267 |
Ziyan Zhang1, Xiaojun Ma1, Xinyan Lian1, Yishan Guo1, Yanqi Song1, Baishu Chang1, Liangqing Luo2.
Abstract
A comprehensive understanding of the relationships between greenhouse gas (GHG) emissions and industrial structure and economic growth holds great significance for China to realize the development of a green economy. This paper calculates GHG emissions based on China's energy consumption, divides the industrial structure in detail, and uses the extended Stochastic Impacts by Regression on Population, Affluence, and Technology model that is realized by PLS method and Tapio decoupling model to study the relationship of GHG emissions to industrial structure and economic growth. The results show that (1) China's total GHG emissions showed a year-on-year growth trend from 2000 to 2017. For CO2, CH4, and N2O, only N2O emission showed a significant downward trend, while CO2 and CH4 emissions showed a slow growth trend. (2) The proportions of added value of industry and construction are positively correlated with GHG emissions, while those of farming, forestry, animal husbandry, and fishery; wholesale and retail trade; transport; and accommodation and catering are negatively correlated with GHG emissions. (3) China's GHG emissions and overall economic growth are in a decoupling state, but in the energy field, N2O emission reduction control has the best effect. Additionally, the overall economic growth of China's industrial sector and GHG emissions have experienced the process of decoupling-link-negative decoupling-link-decoupling. Graphical abstract.Entities:
Keywords: Economic growth; Greenhouse gas emissions; Industrial structure; PLS method; STIRPAT model; Tapio decoupling model
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Year: 2020 PMID: 32700267 DOI: 10.1007/s11356-020-10091-w
Source DB: PubMed Journal: Environ Sci Pollut Res Int ISSN: 0944-1344 Impact factor: 4.223