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PREDICTION OF CARBON EMISSION FROM CULTIVATION IN EASTERN CHINA UNTIL 2035 BASED ON ANALYSIS OF CARBON EMISSION FROM 1998 TO 2018 BY STIRPAT MODEL.

Authors :
SUN, M.
LIU, T. L. X.
YAN, L.
YIN, H. M.
Source :
Applied Ecology & Environmental Research; 2023, Vol. 21 Issue 5, p4323-4341, 19p
Publication Year :
2023

Abstract

It is widely acknowledged that greenhouse gases (GHG) like carbon dioxide (CO<subscript>2</subscript>), nitrous oxide (N<subscript>2</subscript>O), and methane (CH<subscript>4</subscript>) play a key role in the development of global climate change. 17% of China's GHG came from the agricultural industry. For China's future development, it is essential to investigate low-carbon emission paths in planting fields, as one of the key components of agriculture. In this study, the IPCC method was used to estimate the total carbon emission from cultivation in Eastern China. The Tapio decoupling model was used to study the relationship between economic growth and carbon emission. An extended STIRPAT stimulus model was established to predict the carbon emission of the planting industry in East China with three development paths. The results show that carbon emission in East China has shown a fluctuating downward trend with a peak in 1999, which has strong decoupling characteristics with economic growth. Adjusting agricultural structure and raising the mechanization rate can remarkably reduce agricultural carbon emission. Compared to 2020, carbon emission in 2035 will decrease by 12.50%, 13.68%, and 14.32% with Baseline, Low-carbon, and Enhanced Low-carbon scenarios, respectively. Effective measures such as optimizing planting structure by adjusting rice area, promoting intensive mechanization, and improving fertilizer use efficiency can reduce carbon emission actively. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15891623
Volume :
21
Issue :
5
Database :
Complementary Index
Journal :
Applied Ecology & Environmental Research
Publication Type :
Academic Journal
Accession number :
173622659
Full Text :
https://doi.org/10.15666/aeer/2105_43234341